Response Window Research Articles

Engineering modular and tunable single-molecule sensors by decoupling sensing from signal output.

Biosensors play key roles in medical research and diagnostics. However, the development of biosensors for new biomolecular targets of interest often involves tedious optimization steps to ensure a high signal response at the analyte concentration of interest. Here we show a modular nanosensor platform that facilitates these steps by offering ways to decouple and independently tune the signal output as well as the response window. Our approach utilizes a dynamic DNA origami nanostructure to engineer a high optical signal response based on fluorescence resonance energy transfer. We demonstrate mechanisms to tune the sensor's response window, specificity and cooperativity as well as highlight the modularity of the proposed platform by extending it to different biomolecular targets including more complex sensing schemes. This versatile nanosensor platform offers a promising starting point for the rapid development of biosensors with tailored properties.

Moral decision making: Explainable insights into the role of working memory in autonomous driving

The intersection of Artificial Intelligence (AI) and moral philosophy presents unique challenges in the development of autonomous vehicles, particularly in scenarios requiring split-second ethical decisions. This study examines the relationship between working memory (WM) and moral judgments in simulated AV scenarios, quantifying the effects of varying cognitive load on utilitarian decision-making under different time constraints. We experimented with 336 participants, each completing 16 simulated driving trials presenting unique ethical dilemmas. Results reveal a complex interplay between cognitive load and ethical choices. Under high temporal pressure (1-second response window), utilitarian decisions decreased significantly from 92.77 % to 70.08 %. Extended time constraints led to increased utilitarian choices. Statistical analyses validated these findings across diverse ethical contexts. Chi-square tests revealed significant associations between WM load and utilitarian decisions in 1-second conditions, particularly for high-stakes scenarios. Logistic regression showed that WM significantly decreased the likelihood of utilitarian decisions in these scenarios. Six supervised machine learning models were employed, with Gaussian Naive Bayes achieving the highest predictive accuracy (82.2 % to 97.0 %) in distinguishing utilitarian decisions. Partial Dependence analysis revealed a strong negative correlation between WM and utilitarian decisions, especially in the 1-second interval. The 2-second interval emerged as potentially optimal for balancing time constraints and cognitive load. These findings contribute to the theoretical understanding of ethical decision-making under cognitive load and provide practical insights for developing ethically aligned autonomous systems, with implications for improving safety, optimizing takeover protocols, and enhancing the ethical reasoning capabilities of autonomous driving systems.

Poly(3, 4-Ethylenedioxythiophene) as Promising Energy Storage Materials in Zinc-Ion Batteries.

Benefiting from the advantages of high conductivity and good electrochemical stability, the conjugated conducting polymer poly (3, 4-ethylenedioxythiophene) is a promising energy storage material in zinc-ion batteries. Zinc-ion batteries have the advantages of high safety, environmental friendliness, and low cost, but suffer from unstable cathode material structure, poor electrical conductivity, and uncontrollable dendritic growth of zinc anodes. PEDOT, with its fast electrochemical response and wide potential window, is expected to make up for the shortcomings and enhance capacity and cycle life of zinc-ion batteries. Herein, in this review different polymerization methods of poly (3, 4-ethylenedioxythiophene) as well as their structure and properties are summarized; the progress in doping strategies related to the increasing conductivity and dispersivity of poly (3, 4-ethylenedioxythiophene) materials is discussed; specific applications of poly (3, 4-ethylenedioxythiophene)-based materials in anode, cathode, electrolyte, and binder of zinc-ion batteries are explored; and the representative advancements for improving the electrochemical performance of poly (3, 4-ethylenedioxythiophene) in zinc-ion batteries are emphasized. Finally, the current challenges of poly (3, 4-ethylenedioxythiophene) as promising materials in zinc-ion batteries and an insight into their future research directions are pointed out.

Bidirectional Temperature‐Responsive Thermochromic Hydrogels With Adjustable Light Transmission Interval for Smart Windows

AbstractThermochromic smart windows have been widely developed for solar regulation to save building energy. However, most current smart windows still exhibit a single responsiveness to a specific temperature, which is not conducive to daytime energy saving or nighttime privacy protection. Herein, a low‐temperature response is achieved by pre‐initiation of the monomer acrylamide (AAm) and acrylic acid (AA) in the synthesis of P(AAm‐co‐AA). Then, N‐isopropyl acrylamide and AAm are introduced into P(AAm‐co‐AA) to form a pre‐polymerized precursor solution. The liquid precursor solution can be encapsulated within two quartz glasses and synthesized in situ to prepare smart windows, which exhibit a high visible light transmittance of 84.4%, excellent solar modulation of 69.5%, and bidirectional temperature responsiveness (cold and hot). In addition, the upper critical solution temperature and the lower critical solution temperature of the hydrogel and the light transmission interval between the two temperatures can be flexibly adjusted to adapt to different climates and individual user needs. The designed smart window maintains a high light transmission within the human body's comfort temperature range. The bidirectional temperature response window achieves the dual functions of energy saving and privacy protection, making it an ideal smart window candidate with good prospects for practical applications.

Time-course characterization of whole-transcriptome dynamics of HepG2/C3A spheroids and its toxicological implications

Physiologically relevant in vitro models are a priority in predictive toxicology to replace and/or reduce animal experiments. The compromised toxicant metabolism of many immortalized human liver cell lines grown as monolayers as compared to in vivo metabolism limits their physiological relevance. However, recent efforts to culture liver cells in a 3D environment, such as spheroids, to better mimic the in vivo conditions, may enhance the toxicant metabolism of human liver cell lines. In this study, we characterized the dynamic changes in the transcriptome of HepG2/C3A hepatocarcinoma cell spheroids maintained in a clinostat system (CelVivo) to gain insight into the metabolic capacity of this model as a function of spheroid size and culture time. We assessed morphological changes (size, necrotic core), cell health, and proliferation rate from initial spheroid seeding to 35 days of continuous culture in conjunction with a time-course (0, 3, 7, 10, 14, 21, 28 days) of the transcriptome (TempO-Seq, BioSpyder). The phenotypic characteristics of HepG2/C3A growing in spheroids were comparable to monolayer growth until ∼Day 12 (Day 10–14) when a significant decrease in cell doubling rate was noted which was concurrent with down-regulation of cell proliferation and cell cycle pathways over this time period. Principal component analysis of the transcriptome data suggests that the Day 3, 7, and 10 spheroids are pronouncedly different from the Day 14, 21, and 28 spheroids in support of a biological transition time point during the long-term 3D spheroid cultures. The expression of genes encoding cellular components involved in toxicant metabolism and transport rapidly increased during the early time points of spheroids to peak at Day 7 or Day 10 as compared to monolayer cultures with a gradual decrease in expression with further culture, suggesting the most metabolically responsive time window for exposure studies. Overall, we provide baseline information on the cellular and molecular characterization, with a particular focus on toxicant metabolic capacity dynamics and cell growth, of HepG2/C3A 3D spheroid cultures over time.

Imparting insoluble-soluble property to Cyt c by immobilizing Cyt c in UCST-pH dual responsive polymer for highly sensitive detection of phenol

Immobilization of enzymes in porous organic framework (POF) materials is popular strategy to stabilize enzymes. For such solid enzyme catalysis system, improving the catalytic efficiency is challenging due to the diffusion resistance from solid-liquid interface and inner pores. Here, UCST-pH dual responsive polymeric carrier (PEG-b-PAAm-b-P(GMA-co-AAc)) was synthesized to immobilize cytochrome c (Cyt c), which impart the reversibly insoluble-soluble property to the immobilized Cyt c. The PEG-b-PAAm-b-P(GMA-co-AAc) could serve as an insoluble-soluble matrix to fast and efficiently immobilize Cyt c via covalent attachment, achieving a remarkable 92% loading efficiency within just 120min. The obtained insoluble PEG-b-PAAm-b-P(GMA-co-AAc)-Cyt c micelles exhibited an improvement in thermal, pH stability and reusability. The completely soluble PEG-b-PAAm-b-P(GMA-co-AAc)-Cyt c conjugates accelerated substrate diffusion and enhanced the catalytic efficiency. These excellent advantages led to low detection limit (1.99μM), lower than the presently reported biosensors based on enzyme mimics in the colorimetric detection of phenol. This UCST-pH dual responsive window presents a new platform to efficiently control the immobilization and release of enzymes, which will achieve excellent stability and catalytic efficiency.

Low-Cost Classroom and Laboratory Exercises for Investigating Both Wave and Event-Related Electroencephalogram Potentials.

Electroencephalography (EEG) has given rise to a myriad of new discoveries over the last 90 years. EEG is a noninvasive technique that has revealed insights into the spatial and temporal processing of brain activity over many neuroscience disciplines, including sensory, motor, sleep, and memory formation. Most undergraduate students, however, lack laboratory access to EEG recording equipment or the skills to perform an experiment independently. Here, we provide easy-to-follow instructions to measure both wave and event-related EEG potentials using a portable, low-cost amplifier (Backyard Brains, Ann Arbor, MI) that connects to smartphones and PCs, independent of their operating system. Using open-source software (SpikeRecorder) and analysis tools (Python, Google Colaboratory), we demonstrate tractable and robust laboratory exercises for students to gain insights into the scientific method and discover multidisciplinary neuroscience research. We developed 2 laboratory exercises and ran them on participants within our research lab (N = 17, development group). In our first protocol, we analyzed power differences in the alpha band (8-13 Hz) when participants alternated between eyes open and eyes closed states (n = 137 transitions). We could robustly see an increase of over 50% in 59 (43%) of our sessions, suggesting this would make a reliable introductory experiment. Next, we describe an exercise that uses a SpikerBox to evoke an event-related potential (ERP) during an auditory oddball task. This experiment measures the average EEG potential elicited during an auditory presentation of either a highly predictable ("standard") or low-probability ("oddball") tone. Across all sessions in the development group (n=81), we found that 64% (n=52) showed a significant peak in the standard response window for P300 with an average peak latency of 442ms. Finally, we tested the auditory oddball task in a university classroom setting. In 66% of the sessions (n=30), a clear P300 was shown, and these signals were significantly above chance when compared to a Monte Carlo simulation. These laboratory exercises cover the two methods of analysis (frequency power and ERP), which are routinely used in neurology diagnostics, brain-machine interfaces, and neurofeedback therapy. Arming students with these methods and analysis techniques will enable them to investigate this laboratory exercise's variants or test their own hypotheses.

Regulating Arrhenius Activation Energy and Fluorescence Quantum Yields of AuNCs-MOF to Achieve High Temperature Sensitivity in a Wide Response Window.

Luminescent thermometry affords remote measurement of temperature and shows huge potential in future technology beyond those possible with traditional methods. Strategies of temperature measurement aiming to increase thermal sensitivity in a wide temperature response window would represent a pivotal step forward, but most thermometers cannot do both of them. Herein, we propose a balancing strategy to achieve a trade-off between high Arrhenius activation energy (Ea), which could stretch the temperature response windows, and fluorescence quantum yields (QYs) in a manner that will increase thermal sensitivity in a wide response window. In particular, a luminescent thermometer composed of AuNCs-MOF is prepared via a facile impregnation process to enhance QYs and Ea, responsible for high relative sensitivity (Sr) (15.6% K-1) and ultrawide temperature linearity range (from 83 to 343 K), respectively. Taking fluorescence intensity and lifetime as multiple parameters, the maximum Sr can reach 22.4% K-1 by multiple linear regression. The maximum Sr and temperature response range of the proposed thermometer outperform those of the most recent luminescent thermometers. The strategy of balancing Sr and thermal response range by regulating Ea and QYs enables the construction of ultra-accurate thermal sensors in the age of artificial intelligence.

Dynamics and bifurcations in a model of chronic myeloid leukemia with optimal immune response windows.

Chronic Myeloid Leukemia is a blood cancer for which standard therapy with Tyrosine-Kinase Inhibitors is successful in the majority of patients. After discontinuation of treatment half of the well-responding patients either present undetectable levels of tumor cells for a long time or exhibit sustained fluctuations of tumor load oscillating at very low levels. Motivated by the consequent question of whether the observed kinetics reflect periodic oscillations emerging from tumor-immune interactions, in this work, we analyze a system of ordinary differential equations describing the immune response to CML where both the functional response against leukemia and the immune recruitment exhibit optimal activation windows. Besides investigating the stability of the equilibrium points, we provide rigorous proofs that the model exhibits at least two types of bifurcations: a transcritical bifurcation around the tumor-free equilibrium point and a Hopf bifurcation around a biologically plausible equilibrium point, providing an affirmative answer to our initial question. Focusing our attention on the Hopf bifurcation, we examine the emergence of limit cycles and analyze their stability through the calculation of Lyapunov coefficients. Then we illustrate our theoretical results with numerical simulations based on clinically relevant parameters. Besides the mathematical interest, our results suggest that the fluctuating levels of low tumor load observed in CML patients may be a consequence of periodic orbits arising from predator-prey-like interactions.

How the cognitive load of simulated driving affects the brain dynamics underlying auditory attention

Objective Distracted driving is a primary contributor to for motor vehicle crashes, the leading cause for injuries and fatalities for youth. Although attention and working memory clearly underlie driving abilities, few studies explore these functions on the brain-level under the cognitive load of driving. To understand the load driving has on auditory attention processing, we examined the differences in dynamic brain response to auditory stimuli during LOAD (while driving in a high-fidelity driving simulator) and No-LOAD conditions (seated in simulator, parked on the side of the road). Methods Twenty-seven young adult drivers (18–27 y/o; 15 = women) completed a Selective Auditory Attention Task during both a LOAD (driving) and No-LOAD condition in a ½ cab miniSim® high-fidelity driving simulator. During the task, participants responded by pressing the volume control button on the steering wheel when a target tone was presented to a target ear. Electroencephalography-recorded event-related brain responses to the target tones were evaluated through alpha and theta oscillations for two response windows (early: 150–330ms; late: 350–540ms). Results During an early time window, we observed a significant interaction between attended/unattended and LOAD/No-LOAD theta power in the right frontal cortical region (F(1, 24)= 5.4, p=.03, partial η 2=.18). During the later window, we observed a significant interaction between attended/unattended and LOAD/No-LOAD alpha response in the posterior cortical region (F(1, 24)=11.81, p=.002, partial η 2=.15) and in the right temporal cortical region during the window (F(1, 24)=4.3, p=.05, partial η 2=.33). Conclusions Our data provide insight into the demand that driving has on cognitive faculties and how dual task engagement may draw resources away from driving. We suggest future research directly incorporate vehicle control abilities into study design to understand how brain-based measures relate to driving behaviors.

Developmental differences in striatal recruitment by reward prospects as a function of attentional demand

Adolescent risk-taking has been attributed to earlier-developing motivational neurocircuitry that is poorly controlled by immature executive-control neurocircuitry. Functional magnetic resonance imaging findings of increased ventral striatum (VS) recruitment by reward prospects in adolescents compared to adults support this theory. Other studies found blunted VS recruitment by reward-predictive cues in adolescents compared to adults. Task features may explain this discrepancy but have never been systematically explored. Adolescents and adults performed a novel reward task that holds constant the expected value of all rewards but varies whether rewards are dependent on vigilance-intensive responding versus making a lucky choice during a relaxed response window. We examined group by sub-task contrast differences in activation of VS and more motoric regions of striatum in response to anticipatory cues. Reward anticipation in both task conditions activated portions of striatum in both groups. In voxel-wise comparison, adults showed greater anticipatory recruitment of VS in trials involving choice during a relaxed time window, not in the more vigilance-demanding trials as hypothesized. In accord with our hypotheses, however, adults showed greater activation in dorsal striatum and putamen volumes of interest during reward anticipation under vigilance-demanding conditions. Following trial outcome notifications, adolescents showed greater activation of the VS during reward notification but lower activation during loss notification. These data extend findings of cross-sectional age-group differences in incentive-anticipatory recruitment of striatum, by demonstrating in adults relatively greater recruitment of motor effector regions of striatum by attentional and motor demands.

What's in a name: The role of verbalization in reinforcement learning.

(e.g., characters or fractals) and concrete stimuli (e.g., pictures of everyday objects) are used interchangeably in the reinforcement-learning literature. Yet, it is unclear whether the same learning processes underlie learning from these different stimulus types. In two preregistered experiments (N = 50 each), we assessed whether abstract and concrete stimuli yield different reinforcement-learning performance and whether this difference can be explained by verbalization. We argued that concrete stimuli are easier to verbalize than abstract ones, and that people therefore can appeal to the phonological loop, a subcomponent of the working-memory system responsible for storing and rehearsing verbal information, while learning. To test whether this verbalization aids reinforcement-learning performance, we administered a reinforcement-learning task in which participants learned either abstract or concrete stimuli while verbalization was hindered or not. In the first experiment, results showed a more pronounced detrimental effect of hindered verbalization for concrete than abstract stimuli on response times, but not on accuracy. In the second experiment, in which we reduced the response window, results showed the differential effect of hindered verbalization between stimulus types on accuracy, not on response times. These results imply that verbalization aids learning for concrete, but not abstract, stimuli and therefore that different processes underlie learning from these types of stimuli. This emphasizes the importance of carefully considering stimulus types. We discuss these findings in light of generalizability and validity of reinforcement-learning research.

From attentional fluctuations to intentional fluctuations? Monitoring behavior and intraindividual variability in time-based prospective memory.

In sharp contrast to event-based prospective memory (PM), dynamics of (re)allocation of attention between the ongoing and PM tasks have been much less investigated in time-based PM tasks. We propose an in-depth examination of attention allocation in a time-based PM task by jointly analyzing multiple indicators of time-monitoring behavior, net and time-structured intraindividual variability (IIV) in ongoing-task reaction times (OT RTs), and task performance. Results from dynamic structural equation modeling in a lifespan sample of 198 adults (19-86 years) revealed that larger fluctuations in OT RTs (net IIV) predicted poorer OT performance, but fostered a more efficient pattern of time-monitoring behavior (i.e., checking a clock more frequently and strategically, and slowing OT RTs during the PM response window) that, in turn, enhanced PM. Conversely, greater inertia in OT RTs (time-structured IIV) led to fewer clock-checks and poorer PM performance. Focusing attention on time monitoring to enhance PM performance did not detrimentally affect OT accuracy. Instead, participants showed a speed-accuracy tradeoff to optimize both OT and PM accuracies by slowing their OT RTs during the PM response window. This study therefore shows that two concomitant aspects of IIV (net and time-structured IIV) not only predicted time-monitoring behavior, but also OT and PM accuracies differentially, hence advocating for the necessity to consider both aspects of IIV and time monitoring together to better understand attention allocation policies in time-based PM tasks. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Improvement and optimization of coal dust concentration detection technology: Based on the 3σ criterion and the kalman filtering composite algorithm

Due to the inherent time delay in dust concentration data transmission, dust reduction equipment is unable to respond according to the current moment's dust concentration. Hence, the focus of mine dust concentration detection technology extends beyond the current dust concentration to accurately predicting the next moment's dust concentration, allowing a response window for dust reduction equipment, leading to more optimal dust reduction effects. This necessitates the introduction of the Kalman filtering algorithm. Despite the traditional single Kalman filtering algorithm's ability to make certain dust concentration predictions, it is constrained by high-temperature, high-humidity underground environments and electromagnetic pulse signal interference from fan and coal mining machine operations, with an error rate reaching up to 40 %, seriously disrupting underground dust reduction equipment. However, the composite Kalman filtering algorithm incorporating the 3σ rule effectively eliminates bad values and removes instability from the underground environment and noise, rendering it applicable to most complex environments, providing accurate predicted concentrations for dust reduction equipment, and boosting overall universality. This study designed a fusion algorithm based on the Pauta criterion and Kalman filter to further optimize the dust concentration detection technology based on electrostatic induction. The sensor's model and measuring principle were first analyzed, and the initial calibration and precision testing of the sensor using the experimental system were completed. The dust concentration fluctuation characteristics were then modeled with Matlab, and the noise variance was estimated to process and filter the dust concentration data with the Pauta criterion, Kalman filter, and fusion algorithm respectively. The accuracy of the dust concentration sensor was tested again after applying the fusion algorithm, which proved to significantly enhance the stability and accuracy of the electrostatic induction-based dust concentration sensor. This study has critical implications for coal mine dust concentration monitoring and coal miner occupational health protection.

Unraveling phenological and stomatal responses to flash drought and implications for water and carbon budgets

Abstract. In recent years, extreme droughts in the United States have increased in frequency and severity, underlining a need to improve our understanding of vegetation resilience and adaptation. Flash droughts are extreme events marked by the rapid dry down of soils due to lack of precipitation, high temperatures, and dry air. These events are also associated with reduced preparation, response, and management time windows before and during drought, exacerbating their detrimental impacts on people and food systems. Improvements in actionable information for flash drought management are informed by atmospheric and land surface processes, including responses and feedbacks from vegetation. Phenologic state, or growth stage, is an important metric for modeling how vegetation modulates land–atmosphere interactions. Reduced stomatal conductance during drought leads to cascading effects on carbon and water fluxes. We investigate how uncertainty in vegetation phenology and stomatal regulation propagates through vegetation responses during drought and non-drought periods by coupling a land surface hydrology model to a predictive phenology model. We assess the role of vegetation in the partitioning of carbon, water, and energy fluxes during flash drought and carry out a comparison against drought and non-drought periods. We selected study sites in Kansas, USA, that were impacted by the flash drought of 2012 and that have AmeriFlux eddy covariance towers which provide ground observations to compare against model estimates. Results show that the compounding effects of reduced precipitation and high vapor pressure deficit (VPD) on vegetation distinguish flash drought from other drought and non-drought periods. High VPD during flash drought shuts down modeled stomatal conductance, resulting in rates of evapotranspiration (ET), gross primary productivity (GPP), and water use efficiency (WUE) that fall below those of average drought conditions. Model estimates of GPP and ET during flash drought decrease to rates similar to what is observed during the winter, indicating that plant function during drought periods is similar to that of dormant months. These results have implications for improving predictions of drought impacts on vegetation.

Structure-Switching Electrochemical Aptasensor for Rapid, Reagentless, and Single-Step Nanomolar Detection of C-Reactive Protein.

C-reactive protein (CRP) is an acute-phase reactant and sensitive indicator for sepsis and other life-threatening pathologies, including systemic inflammatory response syndrome. Currently, clinical turn-around times for established CRP detection methods take between 30 min to hours or even days from centralized laboratories. Here, we report the development of an electrochemical biosensor using redox probe-tagged DNA aptamers, functionalized onto inexpensive, commercially available screen-printed electrodes. Binding-induced conformational switching of the CRP-targeting aptamer induces a specific and selective signal-ON event, which enables single-step and reagentless detection of CRP in as little as 1 min. The aptasensor limit of detection spans approximately 20-60 nM in 50% human serum with dynamic response windows spanning 1-200 or 1-500 nM (R = 0.97/R = 0.98 respectively). The sensor is stable for at least 1 week and can be reused numerous times, as judged from repeated real-time dosing and dose-response assays. By decoupling binding events from the signal induction mechanism, structure-switching electrochemical aptamer-based sensors provide considerable advantages over their adsorption-based counterparts. Our work expands on the retinue of such sensors reported in the literature and is the first instance of structure-switching electrochemical aptamer-based sensors (SS-EABs) for reagentless, voltammetric CRP detection. We hope this study inspires further investigations into the suitability of SS-EABs for diagnostics, which will aid translational R&D toward fully realized devices aimed at point-of-care applications or for broader use by the public.

Photoswitchable Temperature Nanosensors Based on the Chemical Kinetics of Photochromic Naphthopyran for Live Cell Imaging.

Microscopic temperature imaging holds significant importance in various fields, particularly in the development of nanomaterials for photothermal therapy (PTT). In this study, we present an analytical method to probe cellular temperature based on chemical kinetics and additional luminescence quenching by photoswitchable naphthopyrans. Taking advantage of the rapid ring-closing reaction of naphthopyran, temperature sensing was realized with a linear relationship between the logarithmic decay time constant (ln τ) and the reciprocal temperature (T-1). To create luminescent temperature nanosensors, we harnessed the ability of ring-opened naphthopyran to quench the luminescence of a semiconducting polymer, resulting in a diverse array of probes. Structural modifications on the naphthopyran also provided a way to fine-tune the sensitivity and response window of the nanosensors. The method allowed cellular temperature imaging on a cost-effective fluorescence microscopic setup. As an application, the temperature increase induced by gold nanorods (AuNRs) in cell lysosomes was successfully monitored, laying the foundation for a new class of photoswitchable nanosensors with promising biological applications.

Synthesis and biological profile of 2,3-dihydro[1,3]thiazolo[4,5-b]pyridines, a novel class of acyl-ACP thioesterase inhibitors.

The present work covers novel herbicidal lead structures that contain a 2,3-dihydro[1,3]thiazolo[4,5-b]pyridine scaffold as structural key feature carrying a substituted phenyl side chain. These new compounds show good acyl-ACP thioesterase inhibition in line with strong herbicidal activity against commercially important weeds in broadacre crops, e.g., wheat and corn. The desired substituted 2,3-dihydro[1,3]thiazolo[4,5-b]pyridines were prepared via an optimized BH3-mediated reduction involving tris(pentafluorophenyl)borane as a strong Lewis acid. Remarkably, greenhouse trials showed that some of the target compounds outlined herein display promising control of grass weed species in preemergence application, combined with a dose response window that enables partial selectivity in certain crops.

Discovery and optimization of spirocyclic lactams that inhibit acyl-ACP thioesterase.

There are various methods to control weeds, that represent considerable challenges for farmers around the globe, although applying small molecular compounds is still the most effective and versatile technology to date. In the search for novel chemical entities with new modes-of-action that can control weeds displaying resistance, we have investigated two spirocyclic classes of acyl-ACP thioesterase inhibitors based on X-ray co-crystal structures and subsequent modelling studies. By exploiting scaffold-hopping and isostere concepts, we were able to identify new spirolactam-based lead structures showing promising activity in vivo against commercially important grass weeds in line with strong target affinity. The present work covers a series of novel herbicidal lead structures that contain a spirocyclic lactam as a structural key feature carrying ortho-substituted benzyl or heteroarylmethylene side chains. These new compounds show good acyl-ACP thioesterase inhibition in line with strong herbicidal activity. Glasshouse trials showed that the spirolactams outlined herein display promising control of grass-weed species in pre-emergence application combined with dose-response windows that enable partial selectivity in wheat and corn. Remarkably, some of the novel acyl-ACP thioesterase-inhibitors showed efficacy against resistant grass weeds such as Alopecurus myosuroides and Lolium spp. on competitive levels compared with commercial standards. © 2024 Society of Chemical Industry.

Semitransparent Near‐Infrared Organic Photodetectors: Flexible, Large‐Area, and Physical‐Vapor‐Deposited for Versatile Advanced Optical Applications

AbstractOrganic photodetectors (OPDs) have experienced remarkable performance improvements over the past decade thanks to significant advancements in organic material synthesis and device architecture engineering. In this study, high‐performance near‐infrared (NIR) OPDs with versatile advanced properties, including large detection areas, mechanical flexibility, and high transparency are realized. By incorporating a thin photo‐absorbing layer, functional blocking layers with a large energy gap, and semitransparent electrodes, the OPDs achieve an average visible transmittance (AVT) of up to 53.4% and color rendering index (CRI) of up to 95 within the human vision photopic response window of 380–780 nm. Both the small (6.44 mm2) and large (256 mm2) detection‐area semitransparent OPDs demonstrate an impressive external quantum efficiency (EQE) of 34% and 36%, and specific detectivity (D*) of 1.4 × 1013 and 1.1 × 1012 Jones, respectively, comparable to silicon‐based inorganic photodetectors. As application demonstrations, OPDs with rigid and flexible substrates are employed for NIR imaging and biosensing, respectively. Notably, the flexible semitransparent OPDs are utilized as signal receivers in conjunction with semitransparent NIR organic light‐emitting diodes (OLEDs) operating as signal producers, demonstrating the feasibility of invisible optical communication. These OPDs represent the best‐performing see‐through devices with flexibility, making them promising candidates for integratable, bio‐compatible, and invisible optical‐sensing applications.