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Purpose: To evaluate AZD4635, an adenosine A2A receptor antagonist, as monotherapy or in combination with durvalumab in patients with advanced solid tumors. Patients and Methods: In phase Ia (dose escalation), patients had relapsed/refractory solid tumors; in phase Ib (dose expansion), patients had checkpoint inhibitor–naïve metastatic castration-resistant prostate cancer (mCRPC) or colorectal carcinoma, non–small cell lung cancer with prior anti–PD-1/PD-L1 exposure, or other solid tumors (checkpoint-naïve or prior anti–PD-1/PD-L1 exposure). Patients received AZD4635 monotherapy (75–200 mg once daily or 125 mg twice daily) or in combination with durvalumab (AZD4635 75 or 100 mg once daily). The primary objective was safety; secondary objectives included antitumor activity and pharmacokinetics; exploratory objectives included evaluation of an adenosine gene signature in patients with mCRPC. Results: As of September 8, 2020, 250 patients were treated (AZD4635, n = 161; AZD4635+durvalumab, n = 89). In phase Ia, DLTs were observed with monotherapy (125 mg twice daily; n = 2) and with combination treatment (75 mg; n = 1) in patients receiving nanosuspension. The most common treatment-related adverse events included nausea, fatigue, vomiting, decreased appetite, dizziness, and diarrhea. The RP2D of the AZD4635 capsule formulation was 75 mg once daily, as monotherapy or in combination with durvalumab. The pharmacokinetic profile was dose-proportional, and exposure was adequate to cover target with 100 mg nanosuspension or 75 mg capsule once daily. In patients with mCRPC receiving monotherapy or combination treatment, tumor responses (2/39 and 6/37, respectively) and prostate-specific antigen responses (3/60 and 10/45, respectively) were observed. High versus low blood-based adenosine signature was associated with median progression-free survival of 21 weeks versus 8.7 weeks. Conclusions: AZD4635 monotherapy or combination therapy was well tolerated. Objective responses support additional phase II combination studies in patients with mCRPC.

Data augmentation is an important method for evaluating the robustness of and enhancing the diversity of training data for natural language processing (NLP) models. In this paper, we present NL-Augmenter, a new participatory Python-based natural language (NL) augmentation framework which supports the creation of transformations (modifications to the data) and filters (data splits according to specific features). We describe the framework and an initial set of 117 transformations and 23 filters for a variety of NL tasks annotated with noisy descriptive tags. The transformations incorporate noise, intentional and accidental human mistakes, socio-linguistic variation, semantically-valid style, syntax changes, as well as artificial constructs that are unambiguous to humans. We demonstrate the efficacy of NL-Augmenter by using its transformations to analyze the robustness of popular language models. We find different models to be differently challenged on different tasks, with quasi-systematic score decreases. The infrastructure, datacards, and robustness evaluation results are publicly available on GitHub for the benefit of researchers working on paraphrase generation, robustness analysis, and low-resource NLP. El aumento de datos es un método importante para evaluar la solidez y mejorar la diversidad del entrenamiento datos para modelos de procesamiento de lenguaje natural (NLP). इस लेख में, हम एनएल-ऑगमेंटर का प्रस्ताव करते हैं - एक नया भागी- दारी पूर्वक, पायथन में बनाया गया, लैंग्वेज (एनएल) ऑग्मेंटेशन फ्रेमवर्क जो ट्रांसफॉर्मेशन (डेटा में बदलाव करना) और फीलटर (फीचर्स के अनुसार डेटा का भाग करना) के नीरमान का समर्थन करता है।. 我们描述了NL-Augmenter框架及其初步包含的117种转换和23个过滤器，并 大致标注分类了一系列可适配的自然语言任务. این دگرگونی ها شامل نویز، اشتباهات عمدی و تصادفی انسانی، تنوع اجتماعی-زبانی، سبک معنایی معتبر، تغییرات نحوی و همچنین ساختارهای مصنوعی است که برای انسان ها مبهم است. NL-Augmenterpa allin kaynintam qawachiyku, tikrakuyninku- nata servichikuspayku, chaywanmi qawariyku modelos de lenguaje popular nisqapa allin takyasqa kayninta. Kami menemukan model yang berbeda ditantang secara berbeda pada tugas yang berbeda, dengan penurunan skor kuasi-sistematis. Infrastruktur, kartu data, dan hasil evaluasi ketahanan dipublikasikan tersedia secara gratis di GitHub untuk kepentingan para peneliti yang mengerjakan pembuatan parafrase, analisis ketahanan, dan NLP sumber daya rendah.

Supplementary Figure from Phase Ia/b, Open-Label, Multicenter Study of AZD4635 (an Adenosine A2A Receptor Antagonist) as Monotherapy or Combined with Durvalumab, in Patients with Solid Tumors

Supplementary Table from Phase Ia/b, Open-Label, Multicenter Study of AZD4635 (an Adenosine A2A Receptor Antagonist) as Monotherapy or Combined with Durvalumab, in Patients with Solid Tumors

Purpose:To evaluate AZD4635, an adenosine A2A receptor antagonist, as monotherapy or in combination with durvalumab in patients with advanced solid tumors.Patients and Methods:In phase Ia (dose escalation), patients had relapsed/refractory solid tumors; in phase Ib (dose expansion), patients had checkpoint inhibitor–naïve metastatic castration-resistant prostate cancer (mCRPC) or colorectal carcinoma, non–small cell lung cancer with prior anti–PD-1/PD-L1 exposure, or other solid tumors (checkpoint-naïve or prior anti–PD-1/PD-L1 exposure). Patients received AZD4635 monotherapy (75–200 mg once daily or 125 mg twice daily) or in combination with durvalumab (AZD4635 75 or 100 mg once daily). The primary objective was safety; secondary objectives included antitumor activity and pharmacokinetics; exploratory objectives included evaluation of an adenosine gene signature in patients with mCRPC.Results:As of September 8, 2020, 250 patients were treated (AZD4635, n = 161; AZD4635+durvalumab, n = 89). In phase Ia, DLTs were observed with monotherapy (125 mg twice daily; n = 2) and with combination treatment (75 mg; n = 1) in patients receiving nanosuspension. The most common treatment-related adverse events included nausea, fatigue, vomiting, decreased appetite, dizziness, and diarrhea. The RP2D of the AZD4635 capsule formulation was 75 mg once daily, as monotherapy or in combination with durvalumab. The pharmacokinetic profile was dose-proportional, and exposure was adequate to cover target with 100 mg nanosuspension or 75 mg capsule once daily. In patients with mCRPC receiving monotherapy or combination treatment, tumor responses (2/39 and 6/37, respectively) and prostate-specific antigen responses (3/60 and 10/45, respectively) were observed. High versus low blood-based adenosine signature was associated with median progression-free survival of 21 weeks versus 8.7 weeks.Conclusions:AZD4635 monotherapy or combination therapy was well tolerated. Objective responses support additional phase II combination studies in patients with mCRPC.

Intrinsically ferromagnetic and semiconducting two-dimensional (2D) H-phase vanadium disulfide (VS2) holds tremendous promise for future electronics, optoelectronics, spintronics and valleytronics applications. However, its thermodynamic instability and the formation of intermediate stoichiometric polymorphs during its growth have stymied any progress towards synthesis of high quality 2D VS2 films. In this article, we circumvent these challenges and accomplish large area growth of monolayer VS2 films using atmospheric pressure chemical vapor deposition (APCVD) technique. By incorporating excess sulfur during the growth process which suppresses the formation of intermediate compounds, good quality large-area VS2 film can be synthesized. Furthermore, the electronic and optoelectronic properties of VS2 were explored by fabricating photosensitive memtransistor devices, which reveal an n-type carrier transport along with a high responsivity to red, green, and blue wavelengths of light. In addition the device exhibited multiple non-volatile conductance states through electrical programming. To the best of our knowledge, this is the first comprehensive report on memtransistors built from large area grown H-phase VS2 that integrate compute, sense, and storage functionalities in a single device.

Vasoactive intestinal peptide (VIP) is a neuropeptide that is produced by the lymphoid cells and plays a major role in immunological functions for controlling the homeostasis of the immune system. VIP has been identified as a potent anti-inflammatory factor, in boosting both innate and adaptive immunity. Since December 2019, SARS‐Cov‐2 was found responsible for the disease COVID‐19 which has spread worldwide. No specific therapies or 100% effective vaccines are yet available for the treatment of COVID‐19. Drug repositioning may offer a strategy and several drugs have been repurposed, including lopinavir/ritonavir, remdesivir, favipiravir, and tocilizumab. This paper describes the main pharmacological properties of synthetic VIP drug (Aviptadil) which is now under clinical trials. A patented formulation of vasoactive intestinal polypeptide (VIP), named RLF-100 (Aviptadil), was developed and finally got approved for human trials by FDA in 2001 and in European medicines agency in 2005. It was awarded Orphan Drug Designation in 2001 by the US FDA for the treatment of acute respiratory distress syndrome and for the treatment of pulmonary arterial hypertension in 2005. Investigational new drug (IND) licenses for human trials of Aviptadil was guaranteed by both the US FDA and EMEA. Preliminary clinical trials seem to support Aviptadil’s benefit. However, such drugs like Aviptadil in COVID‐19 patients have peculiar safety profiles. Thus, adequate clinical trials are necessary for these compounds.

Detecting a potential collision at night is a challenging task owing to the lack of discernible features that can be extracted from the available visual stimuli. To alert the driver or, alternatively, the maneuvering system of an autonomous vehicle, current technologies utilize resource draining and expensive solutions such as light detection and ranging (LiDAR) or image sensors coupled with extensive software running sophisticated algorithms. In contrast, insects perform the same task of collision detection with frugal neural resources. Even though the general architecture of separate sensing and processing modules is the same in insects and in image-sensor-based collision detectors, task-specific obstacle avoidance algorithms allow insects to reap substantial benefits in terms of size and energy. Here, we show that insect-inspired collision detection algorithms, when implemented in conjunction with in-sensor processing and enabled by innovative optoelectronic integrated circuits based on atomically thin and photosensitive memtransistor technology, can greatly simplify collision detection at night. The proposed collision detector eliminates the need for image capture and image processing yet demonstrates timely escape responses for cars on collision courses under various real-life scenarios at night. The collision detector also has a small footprint of ∼40 μm

MEDI4276 is a biparatopic tetravalent antibody targeting two nonoverlapping epitopes in subdomains 2 and 4 of the HER2 ecto-domain, with site-specific conjugation to a tubulysin-based microtubule inhibitor payload. MEDI4276 demonstrates enhanced cellular internalization and cytolysis of HER2-positive tumor cells in vitro. This was a first-in-human, dose-escalation clinical trial in patients with HER2-positive advanced or metastatic breast cancer or gastric cancer. MEDI4276 doses escalated from 0.05 to 0.9 mg/kg (60- to 90-minute intravenous infusion every 3 weeks). Primary endpoints were safety and tolerability; secondary endpoints included antitumor activity (objective response, progression-free survival, and overall survival), pharmacokinetics, and immunogenicity. Forty-seven patients (median age 59 years; median of seven prior treatment regimens) were treated. The maximum tolerated dose was exceeded at 0.9 mg/kg with two patients experiencing dose-limiting toxicities (DLTs) of grade 3 liver function test (LFT) increases, one of whom also had grade 3 diarrhea, which resolved. Two additional patients reported DLTs of grade 3 LFT increases at lower doses (0.4 and 0.6 mg/kg). The most common (all grade) drug-related adverse events (AEs) were nausea (59.6%), fatigue (44.7%), aspartate aminotransferase (AST) increased (42.6%), and vomiting (38.3%). The most common grade 3/4 drug-related AE was AST increased (21.3%). Five patients had drug-related AEs leading to treatment discontinuation. In the as-treated population, there was one complete response (0.5 mg/kg; breast cancer), and two partial responses (0.6 and 0.75 mg/kg; breast cancer)—all had prior trastuzumab, pertuzumab, and ado-trastuzumab emtansine (T-DM1). MEDI4276 has demonstrable clinical activity but displays intolerable toxicity at doses >0.3 mg/kg.

The representation of external stimuli in the form of action potentials or spikes constitutes the basis of energy efficient neural computation that emerging spiking neural networks (SNNs) aspire to imitate. With recent evidence suggesting that information in the brain is more often represented by explicit firing times of the neurons rather than mean firing rates, it is imperative to develop novel hardware that can accelerate sparse and spike-timing-based encoding. Here a medium-scale integrated circuit composed of two cascaded three-stage inverters and one XOR logic gate fabricated using a total of 21 memtransistors based on photosensitive 2D monolayer MoS

Collision detection under poor illumination and nightly conditions pose significant challenge for manned and unmanned vehicles, flying drones, and robots navigating complex terrestrial and extraterrestrial geographies. Existing night vision cameras offer solution based on sophisticated enhancement algorithms or additional thermal sensors necessitating extensive and expensive hardware, which make them power-hungry and untenable for deployment in remote and resource constrained locations. In contrast, nocturnal flying insects can avoid collision using very limited neural resources. Insect-inspired collision detectors based on silicon complementary metal oxide semiconductor technology and field programmable gate arrays also exist, however, the physical separation between sensing and compute and absence of spike-based information processing capability increases their area and energy overhead. Here, we introduce an insect-inspired, spike-based, and in-sensor collision detector using a reconfigurable optoelectronic integrated circuit constructed based on atomically-thin and light-sensitive memtransistors. We imitate the escape response of lobula giant movement detector (LGMD) neuron found in many insect species and demonstrate timely collision detection for various real-life scenarios at night involving cars on collision course. Our collision detector has a small effective footprint of 40 µm2 and consumes miniscule energy of few hundreds pico-Joules.