Comprehensive analysis of metal(loid)s and associated metal(loid) resistance genes in atmospheric particulate matter.

Despite global concerns about metal(loid)s in atmospheric particulate matter (PM), the presence of metal(loid) resistance genes (MRGs) in PM remains unknown. Therefore, we conducted a comprehensive investigation of the metal(loid)s and associated MRGs in PMs in two seasons (summer and winter) in Xiamen, China. According to the geoaccumulation index (Igeo), most metal(loid)s, except for V and Mn, exhibited enrichment in PM, suggesting potential anthropogenic sources. By employing Positive Matrix Factorization (PMF) model, utilizing a dataset encompassing both total and bioaccessible metal(loid)s, along with backward trajectory simulations, traffic emissions were determined to be the primary potential contributor of metal(loid)s in summer, whereas coal combustion was observed to have a dominant contribution in winter. The major contributor to the carcinogenic risk of metal(loid)s in both summer and winter was predominantly attributed to coal combustion, which serves as the main source of bioaccessible Cr. Bacterial communities within PMs showed lower diversity and network complexity in summer than in winter, with Pseudomonadales being the dominant order. Abundant MRGs, including the As(III) S-adenosylmethionine methyltransferase gene (arsM), Cu(I)-translocating P-type ATPase gene (copA), Zn(II)/Cd(II)/Pb(II)-translocating P-type ATPase gene (zntA), and Zn(II)-translocating P-type ATPase gene (ziaA), were detected within the PMs. Seasonal variations were observed for the metal(loid) concentration, bacterial community structure, and MRG abundance. The bacterial community composition and MRG abundance within PMs were primarily influenced by temperature, rather than metal(loid)s. This research offers novel perspectives on the occurrence of metal(loid)s and MRGs in PMs, thereby contributing to the control of air pollution.

General strategy for developing thick-film micro-thermoelectric coolers from material fabrication to device integration.

Micro-thermoelectric coolers are emerging as a promising solution for high-density cooling applications in confined spaces. Unlike thin-film micro-thermoelectric coolers with high cooling flux at the expense of cooling temperature difference due to very short thermoelectric legs, thick-film micro-thermoelectric coolers can achieve better comprehensive cooling performance. However, they still face significant challenges in both material preparation and device integration. Herein, we propose a design strategy which combines Bi2Te3-based thick film prepared by powder direct molding with micro-thermoelectric cooler integrated via phase-change batch transfer. Accurate thickness control and relatively high thermoelectric performance can be achieved for the thick film, and the high-density-integrated thick-film micro-thermoelectric cooler exhibits excellent performance with maximum cooling temperature difference of 40.6 K and maximum cooling flux of 56.5 W·cm-2 at room temperature. The micro-thermoelectric cooler also shows high temperature control accuracy (0.01 K) and reliability (over 30000 cooling cycles). Moreover, the device demonstrates remarkable capacity in power generation with normalized power density up to 214.0 µW · cm-2 · K-2. This study provides a general and scalable route for developing high-performance thick-film micro-thermoelectric cooler, benefiting widespread applications in thermal management of microsystems.

Robust vibrational coherence protected by a core-shell structure in silver nanoclusters.

Vibrational coherence has attracted considerable research interests because of its potential functions in light harvesting systems. Although positive signs of vibrational coherence in metal nanoclusters have been observed, the underlying mechanism remains to be verified. Here, we demonstrate that robust vibrational coherence with a lifetime of 1 ps can be clearly identified in Ag44(SR)30 core-shell nanoclusters, in which an icosahedral Ag12 core is well protected by a dodecahedral Ag20 cage. Ultrafast spectroscopy reveals that two vibrational modes at around 2.4 THz and 1.6 THz, corresponding to the breathing mode and quadrupolar-like mode of the icosahedral Ag12 core, respectively, are responsible for the generation of vibrational coherence. In addition, the vibrational coherence of Ag44 has an additional high frequency mode (2.4 THz) when compared with that of Ag29, in which there is only one low frequency vibration mode (1.6 THz), and the relatively faster dephasing in two-layer Ag29 relative to that in Ag44 further supports the fact that the robust vibrational coherence in Ag44 is ascribed to its unique matryoshka-like core-shell structure. Our findings not only present unambiguous experimental evidence for a multi-layer core-shell structure protected vibrational coherence under ambient conditions but also offers a practical strategy for the design of highly efficient quantum optoelectronic devices.

Optimizing differential expression analysis for proteomics data via high-performing rules and ensemble inference.

Identification of differentially expressed proteins in a proteomics workflow typically encompasses five key steps: raw data quantification, expression matrix construction, matrix normalization, missing value imputation (MVI), and differential expression analysis. The plethora of options in each step makes it challenging to identify optimal workflows that maximize the identification of differentially expressed proteins. To identify optimal workflows and their common properties, we conduct an extensive study involving 34,576 combinatoric experiments on 24 gold standard spike-in datasets. Applying frequent pattern mining techniques to top-ranked workflows, we uncover high-performing rules that demonstrate optimality has conserved properties. Via machine learning, we confirm optimal workflows are indeed predictable, with average cross-validation F1 scores and Matthew's correlation coefficients surpassing 0.84. We introduce an ensemble inference to integrate results from individual top-performing workflows for expanding differential proteome coverage and resolve inconsistencies. Ensemble inference provides gains in pAUC (up to 4.61%) and G-mean (up to 11.14%) and facilitates effective aggregation of information across varied quantification approaches such as topN, directLFQ, MaxLFQ intensities, and spectral counts. However, further development and evaluation are needed to establish acceptable frameworks for conducting ensemble inference on multiple proteomics workflows.

Co-Mutations and Possible Variation Tendency of the Spike RBD and Membrane Protein in SARS-CoV-2 by Machine Learning.

Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, SARS-CoV-2 variants capable of breakthrough infections have attracted global attention. These variants have significant mutations in the receptor-binding domain (RBD) of the spike protein and the membrane (M) protein, which may imply an enhanced ability to evade immune responses. In this study, an examination of co-mutations within the spike RBD and their potential correlation with mutations in the M protein was conducted. The EVmutation method was utilized to analyze the distribution of the mutations to elucidate the relationship between the mutations in the spike RBD and the alterations in the M protein. Additionally, the Sequence-to-Sequence Transformer Model (S2STM) was employed to establish mapping between the amino acid sequences of the spike RBD and M proteins, offering a novel and efficient approach for streamlined sequence analysis and the exploration of their interrelationship. Certain mutations in the spike RBD, G339D-S373P-S375F and Q493R-Q498R-Y505, are associated with a heightened propensity for inducing mutations at specific sites within the M protein, especially sites 3 and 19/63. These results shed light on the concept of mutational synergy between the spike RBD and M proteins, illuminating a potential mechanism that could be driving the evolution of SARS-CoV-2.

Electroacupuncture modulates abnormal brain connectivity after ischemia reperfusion injury in rats: A graph theory-based approach.

BACKGROUND: Electroacupuncture (EA) has been shown to facilitate brain plasticity-related functional recovery following ischemic stroke. The functional magnetic resonance imaging technique can be used to determine the range and mode of brain activation. After stroke, EA has been shown to alter brain connectivity, whereas EA's effect on brain network topology properties remains unclear. An evaluation of EA's effects on global and nodal topological properties in rats with ischemia reperfusion was conducted in this study. METHODS AND RESULTS: There were three groups of adult male Sprague-Dawley rats: sham-operated group (sham group), middle cerebral artery occlusion/reperfusion (MCAO/R) group, and MCAO/R plus EA (MCAO/R + EA) group. The differences in global and nodal topological properties, including shortest path length, global efficiency, local efficiency, small-worldness index, betweenness centrality (BC), and degree centrality (DC) were estimated. Graphical network analyses revealed that, as compared with the sham group, the MCAO/R group demonstrated a decrease in BC value in the right ventral hippocampus and increased BC in the right substantia nigra, accompanied by increased DC in the left nucleus accumbens shell (AcbSh). The BC was increased in the right hippocampus ventral and decreased in the right substantia nigra after EA intervention, and MCAO/R + EA resulted in a decreased DC in left AcbSh compared to MCAO/R. CONCLUSION: The results of this study provide a potential basis for EA to promote cognitive and motor function recovery after ischemic stroke.

Experimental investigation and thermodynamic analysis of application of hybrid nanofluid in a parabolic solar trough collector.

In this research, thermal modeling has been done to investigate the effect of nanofluid on the performance of the linear parabolic collector. Therminol vapor/liquid phase fluid (VP-1) has been used as a base fluid; iron oxide nanoparticles have been used to produce mono-nanofluid; and iron oxide multi-walled carbon nanotubes nanocomposite has been used as nanoparticles to produce hybrid nanofluid. The fluid flow inside the absorber tube of the collector is assumed to be turbulent. The results show that when hybrid nanofluid and mono-nanofluid are used, the energy and exergy efficiencies of the collector are higher than those for the conditions of using the base fluid, but their amount is slightly lower with the use of hybrid nanofluid than when the working fluid is mono-nanofluid. According to the obtained results, the highest energy efficiency of the linear parabolic collector using nanofluid and mono-nanofluid is 70.2% and 70.4%, respectively, and the highest exergy efficiency is 35.7% and 35.9%, respectively. Despite this, the friction coefficient of mono-nanofluid compared to hybrid nanofluid was obtained on average about 9% higher. The results showed that the criterion for evaluating the performance of the collector (hydrodynamic thermal efficiency) when hybrid nanofluid is used is more than when mono-nanofluid is used.

High-performance GeSi/Ge multi-quantum well photodetector on a Ge-buffered Si substrate.

This work demonstrates a high-performance photodetector with a 4-cycle Ge0.86Si0.14/Ge multi-quantum well (MQW) structure grown by reduced pressure chemical vapor deposition techniques on a Ge-buffered Si (100) substrate. At -1 V bias, the dark current density of the fabricated PIN mesa devices is as low as 3 mA/cm2, and the optical responsivities are 0.51 and 0.17 A/W at 1310 and 1550 nm, respectively, corresponding to the cutoff wavelength of 1620 nm. At the same time, the device has good high-power performance and continuous repeatable light response. On the other hand, the temperature coefficient of resistance (TCR) of the device is as high as -5.18%/K, surpassing all commercial thermal detectors. These results indicate that the CMOS-compatible and low-cost Ge0.86Si0.14/Ge multilayer structure is promising for short-wave infrared and uncooled infrared imaging.

Electrochemical ring-opening carboxylation of cyclic carbonate with carbon dioxide.

Electroreductive ring-opening carboxylation of styrene carbonates with CO2 to achieve dicarboxylic acids and/or ß-hydroxy acids has been developed via the selective cleavage of the C(sp3)-O bond in cyclic carbonates. The product selectivity is probably determined by the stability and reactivity of the key benzylic radical and carbanion intermediate.

Clinical gait analysis in older children with autism spectrum disorder.

Individuals with autism spectrum disorder (ASD) often exhibit motor deficits that increase their risk of falls. There is a lack of understanding regarding gait biomechanics demonstrated by older children with ASD. The purpose of the study was to determine differences in gait patterns between older children with ASD and typically developing children. Eleven children with ASD and 11 age- and gender-matched typically developing children were recruited for the study. Participants walked on a force-instrumented treadmill at a constant speed (1.1 â€‹m/s â€‹- â€‹1.2 â€‹m/s) for five minutes (min). Participants performed maximal voluntary contractions to assess their knee muscular strength. Differences between individuals with ASD and matched control participants were examined through paired t-tests with a significance level of p â€‹≤ â€‹0.05. Individuals with ASD demonstrated a smaller knee extensor torque compared to controls (p â€‹= â€‹0.002). Participants with ASD exhibited a shorter stride length (p â€‹= â€‹0.04), a greater cadence (p â€‹= â€‹0.03), and a higher variation in stride width (p â€‹= â€‹0.04) compared to control participants. The individuals with ASD experienced a greater braking ground reaction force (p â€‹= â€‹0.03) during loading response. The results indicate older children with ASD develop a unique gait pattern signified by a reduced stride length, increased cadence, and an increase of variation in stride width. This unique gait pattern may represent a movement strategy used by the individuals with ASD to compensate for the weakness associated with their knee extensor muscles. Individuals with ASD who demonstrate these unique gait deviations may face reduced postural stability and an increased risk of fall-related injuries.

Prenatal diagnosis of chromosomal aberrations by chromosomal microarray analysis and pregnancy outcomes of fetuses with polyhydramnios.

OBJECTIVES: To explore the prenatal clinical utility of chromosome microarray analysis (CMA) for polyhydramnios and evaluate the short and long-term prognosis of fetuses with polyhydramnios. METHODS: A total of 600 singleton pregnancies with persistent polyhydramnios from 2014 to 2020 were retrospectively enrolled in this study. All cases received amniocentesis and were subjected to CMA results. All cases were categorized into two groups: isolated polyhydramnios and non-isolated polyhydramnios [with soft marker(s) or with sonographic structural anomalies]. All fetuses were followed up from 6 months to five years after amniocentesis to acquire short and long-term prognosis. RESULTS: The detection rates of either aneuploidy or pathogenic copy number variants in fetuses with non-isolated polyhydramnios were significantly higher than those with isolated polyhydramnios (5.0 vs. 1.5%, p = 0.0243; 3.6 vs. 0.8%, p = 0.0288). The detection rate of total chromosomal abnormalities in the structural abnormality group was significantly higher than that in the isolated group (10.0 vs. 2.3%, p = 0.0003). In the CMA-negative cases, the incidence of termination of pregnancy, neonatal and childhood death, and non-neurodevelopmental disorders in fetuses combined with structural anomalies was significantly higher than that in fetuses with isolated polyhydramnios (p < 0.05). We did not observe any difference in the prognosis between the isolated group and the combined group of ultrasound soft markers. In addition, the risk of postnatal neurodevelopmental disorders was also consistent among the three groups (1.6 vs. 1.3 vs. 1.8%). CONCLUSION: For low-risk pregnancies, invasive prenatal diagnosis of isolated polyhydramnios might be unnecessary. CMA should be considered for fetuses with structural anomalies. In CMA-negative cases, the prognosis of fetuses with isolated polyhydramnios was good, and polyhydramnios itself did not increase the risk of postnatal neurological development disorders. The worse prognosis mainly depends on the combination of polyhydramnios with structural abnormalities.

Non-coding RNAs as regulators of the Hippo pathway in cardiac development and cardiovascular disease.

Cardiovascular diseases pose a serious threat to human health. The onset of cardiovascular diseases involves the comprehensive effects of multiple genes and environmental factors, and multiple signaling pathways are involved in regulating the occurrence and development of cardiovascular diseases. The Hippo pathway is a highly conserved signaling pathway involved in the regulation of cell proliferation, apoptosis, and differentiation. Recently, it has been widely studied in the fields of cardiovascular disease, cancer, and cell regeneration. Non-coding RNA (ncRNAs), which are important small molecules for the regulation of gene expression in cells, can directly target genes and have diverse regulatory functions. Recent studies have found that ncRNAs interact with Hippo pathway components to regulate myocardial fibrosis, cardiomyocyte proliferation, apoptosis, and hypertrophy and play an important role in cardiovascular disease. In this review, we describe the mode of action of ncRNAs in regulating the Hippo pathway, provide new ideas for further research, and identify molecules involved in the mechanism of action of ncRNAs and the Hippo pathway as potential therapeutic targets, with the aim of finding new modes of action for the treatment and prevention of cardiovascular diseases.

Alterations of human CSF and serum-based mitophagy biomarkers in the continuum of Alzheimer disease.

Defective mitophagy is consistently found in postmortem brain and iPSC-derived neurons from Alzheimer disease (AD) patients. However, there is a lack of extensive examination of mitophagy status in serum or cerebrospinal fluid (CSF), and the clinical potential of mitophagy biomarkers has not been tested. We quantified biomarkers of mitophagy/autophagy and lysosomal degradation (PINK1, BNIP3L and TFEB) in CSF and serum from 246 individuals, covering mild cognitive impairment due to AD (MCI-AD, n = 100), dementia due to AD (AD-dementia, n = 100), and cognitively unimpaired individuals (CU, n = 46), recruited from the Czech Brain Aging Study. Cognitive function and brain atrophy were also assessed. Our data show that serum and CSF PINK1 and serum BNIP3L were higher, and serum TFEB was lower in individuals with AD than in corresponding CU individuals. Additionally, the magnitude of mitophagy impairment correlated with the severity of clinical indicators in AD patients. Specifically, levels of PINK1 positively correlated with phosphorylated (p)-MAPT/tau (181), total (t)-MAPT/tau, NEFL (neurofilament light chain), and NRGN (neurogranin) levels in CSF and negatively with memory, executive function, and language domain. Serum TFEB levels negatively correlated with NEFL and positively with executive function and language. This study reveals mitophagy impairment reflected in biofluid biomarkers of individuals with AD and associated with more advanced AD pathology.Abbreviation: Aß: amyloid beta; AD: Alzheimer disease; AVs: autophagic vacuoles; BNIP3L: BCL2 interacting protein 3 like; CU: cognitively unimpaired; CSF: cerebrospinal fluid; LAMP1: lysosomal-associated membrane protein 1; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MCI: mild cognitive impairment; NRGN: neurogranin; NEFL: neurofilament light chain; p-MAPT/tau: phosphorylated microtubule associated protein tau; PINK1: PTEN induced kinase 1; t-MAPT/tau: total microtubule associated protein tau; TFEB: transcription factor EB; TMT: Trail Making Test.

Extravascular administration of IGF1R antagonists protects against aortic aneurysm in rodent and porcine models.

An abdominal aortic aneurysm (AAA) is a life-threatening cardiovascular disease. We identified plasma insulin-like growth factor 1 (IGF1) as an independent risk factor in patients with AAA by correlating plasma IGF1 with risk. Smooth muscle cell- or fibroblast-specific knockout of Igf1r, the gene encoding the IGF1 receptor (IGF1R), attenuated AAA formation in two mouse models of AAA induced by angiotensin II infusion or CaCl2 treatment. IGF1R was activated in aortic aneurysm samples from human patients and mice with AAA. Systemic administration of IGF1C, a peptide fragment of IGF1, 2 weeks after disease development inhibited AAA progression in mice. Decreased AAA formation was linked to competitive inhibition of IGF1 binding to its receptor by IGF1C and modulation of downstream alpha serine/threonine protein kinase (AKT)/mammalian target of rapamycin signaling. Localized application of an IGF1C-loaded hydrogel was developed to reduce the side effects observed after systemic administration of IGF1C or IGF1R antagonists in the CaCl2-induced AAA mouse model. The inhibitory effect of the IGF1C-loaded hydrogel administered at disease onset on AAA formation was further evaluated in a guinea pig-to-rat xenograft model and in a sheep-to-minipig xenograft model of AAA formation. The therapeutic efficacy of IGF1C for treating AAA was tested through extravascular delivery in the sheep-to-minipig model with AAA established for 2 weeks. Percutaneous injection of the IGF1C-loaded hydrogel around the AAA resulted in improved vessel flow dynamics in the minipig aorta. These findings suggest that extravascular administration of IGF1R antagonists may have translational potential for treating AAA.

Diagnostic Value of Clear Cell Likelihood Score v1.0 and v2.0 for Common Subtypes of Small Renal Masses: A Multicenter Comparative Study.

BACKGROUND: Clear cell likelihood score (ccLS) is reliable for diagnosing small renal masses (SRMs). However, the diagnostic value of Clear cell likelihood score version 1.0 (ccLS v1.0) and v2.0 for common subtypes of SRMs might be a potential score extension. PURPOSE: To compare the diagnostic performance and interobserver agreement of ccLS v1.0 and v2.0 for characterizing five common subtypes of SRMs. STUDY TYPE: Retrospective. POPULATION: 797 patients (563 males, 234 females; mean age, 53 ± 12 years) with 867 histologically proven renal masses. FIELD STRENGTH/SEQUENCES: 3.0 and 1.5 T/T2 weighted imaging, T1 weighted imaging, diffusion-weighted imaging, a dual-echo chemical shift (in- and opposed-phase) T1 weighted imaging, multiphase dynamic contrast-enhanced imaging. ASSESSMENT: Six abdominal radiologists were trained in the ccLS algorithm and independently scored each SRM using ccLS v1.0 and v2.0, respectively. All SRMs had definite pathological results. The pooled area under curve (AUC), accuracy, sensitivity, and specificity were calculated to evaluate the diagnostic performance of ccLS v1.0 and v2.0 for characterizing common subtypes of SRMs. The average κ values were calculated to evaluate the interobserver agreement of the two scoring versions. STATISTICAL TESTS: Random-effects logistic regression; Receiver operating characteristic analysis; DeLong test; Weighted Kappa test; Z test. The statistical significance level was P < 0.05. RESULTS: The pooled AUCs of clear cell likelihood score version 2.0 (ccLS v2.0) were statistically superior to those of ccLS v1.0 for diagnosing clear cell renal cell carcinoma (ccRCC) (0.907 vs. 0.851), papillary renal cell carcinoma (pRCC) (0.926 vs. 0.888), renal oncocytoma (RO) (0.745 vs. 0.679), and angiomyolipoma without visible fat (AMLwvf) (0.826 vs. 0.766). Interobserver agreement for SRMs between ccLS v1.0 and v2.0 is comparable and was not statistically significant (P = 0.993). CONCLUSION: The diagnostic performance of ccLS v2.0 surpasses that of ccLS v1.0 for characterizing ccRCC, pRCC, RO, and AMLwvf. Especially, the standardized algorithm has optimal performance for ccRCC and pRCC. ccLS has potential as a supportive clinical tool. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 2.

Targeting the chromatin structural changes of antitumor immunity.

Epigenomic imbalance drives abnormal transcriptional processes, promoting the onset and progression of cancer. Although defective gene regulation generally affects carcinogenesis and tumor suppression networks, tumor immunogenicity and immune cells involved in antitumor responses may also be affected by epigenomic changes, which may have significant implications for the development and application of epigenetic therapy, cancer immunotherapy, and their combinations. Herein, we focus on the impact of epigenetic regulation on tumor immune cell function and the role of key abnormal epigenetic processes, DNA methylation, histone post-translational modification, and chromatin structure in tumor immunogenicity, and introduce these epigenetic research methods. We emphasize the value of small-molecule inhibitors of epigenetic modulators in enhancing antitumor immune responses and discuss the challenges of developing treatment plans that combine epigenetic therapy and immunotherapy through the complex interaction between cancer epigenetics and cancer immunology.

An Artificial Enzyme for Asymmetric Nitrocyclopropanation of α,ß-Unsaturated Aldehydes-Design and Evolution.

The introduction of an abiological catalytic group into the binding pocket of a protein host allows for the expansion of enzyme chemistries. Here, we report the generation of an artificial enzyme by genetic encoding of a non-canonical amino acid that contains a secondary amine side chain. The non-canonical amino acid and the binding pocket function synergistically to catalyze the asymmetric nitrocyclopropanation of α,ß-unsaturated aldehydes by the iminium activation mechanism. The designer enzyme was evolved to an optimal variant that catalyzes the reaction at high conversions with high diastereo- and enantioselectivity. This work demonstrates the application of genetic code expansion in enzyme design and expands the scope of enzyme-catalyzed abiological reactions.

Thermodynamically and Kinetically Enhanced Benzene Vapor Sensor Based on the Cu-TCPP-Cu MOF with Extremely Low Limit of Detection.

As a carcinogenic and highly neurotoxic hazardous gas, benzene vapor is particularly difficult to be distinguished in BTEX (benzene, toluene, ethylbenzene, xylene) atmosphere and be detected in low concentrations due to its chemical inertness. Herein, we develop a depth-related pore structure in Cu-TCPP-Cu to thermodynamically and kinetically enhance the adsorption of benzene vapor and realize the detection of ultralow-temperature benzene gas. We find that the in-plane π electronic nature and proper pore sizes in Cu-TCPP-Cu can selectively induce the adsorption and diffusion of BTEX. Interestingly, the theoretical calculations (including density functional theory (DFT) and grand canonical Monte Carlo (GCMC) simulations) exhibit that benzene molecules are preferred to adsorb and array as a consecutive arrangement mode in the Cu-TCPP-Cu pore, while the TEX (toluene, ethylbenzene, xylene) dominate the jumping arrangement model. The differences in distribution behaviors can allow adsorption and diffusion of more benzene molecules within limited room. Furthermore, the optimal pore-depth range (60-65 nm) of Cu-TCPP-Cu allows more exposure of active sites and hinders the gas-blocking process. The optimized sensor exhibits ultrahigh sensitivity to benzene vapor (155 Hz/µg@1 ppm), fast response time (less than 10 s), extremely low limit of detection (65 ppb), and excellent selectivity (83%). Our research thus provides a fundamental understanding to design and optimize two-dimensional metal-organic framework (MOF)-based gas sensors.

Getting stuck in a rut as an emergent feature of a dynamic decision-making system.

Human sensorimotor decision making has a tendency to get 'stuck in a rut', being biased towards selecting a previously implemented action structure (hysteresis). Existing explanations propose this is the consequence of an agent efficiently modifying an existing plan, rather than creating a new plan from scratch. Instead, we propose that hysteresis is an emergent property of a system learning from the consequences of its actions. To examine this, 152 participants moved a cursor to a target on a tablet device while avoiding an obstacle. Hysteresis was observed when the obstacle moved sequentially across the screen between trials, whereby the participant continued moving around the same side of the obstacle despite it now requiring a larger movement than the alternative. Two further experiments (n = 20) showed an attenuation when time and resource constraints were eased. We created a simple computational model capturing probabilistic estimate updating that showed the same patterns of results. This provides, to our knowledge, the first computational demonstration of how sensorimotor decision making can get 'stuck in a rut' through the updating of the probability estimates associated with actions.