Inhibitory effect of host ocular microenvironmental factors on chlorhexidine digluconate activity.

Acanthamoeba spp. are free-living protozoan that cause a serious human eye disease called Acanthamoeba keratitis (AK). Several new and effective medical therapy for AK patients remains highly debated and therefore, CHG is still considered one of the first lines of treatment for AK patients. We hypothesized that ocular microenvironmental factors are responsible for Acanthamoeba drug resistance and clinical AK treatment failure. To investigate the influence of the ocular surface on CHG treatment, we tested the effect of several ocular elements on the anti-amoeba activity of CHG. The suspected inhibitory elements, including mucin, albumin, human and amoeba cell lysates, live and heat-killed bacteria, and cornea, were added to the amoebicidal activity platform, where amoeba was incubated with CHG at varying concentrations. Mucin showed a significant inhibitory effect on CHG activity against Acanthamoeba castellanii In contrast, albumin did not affect CHG treatment. Furthermore, human and amoeba cell lysates as well as live and heat-killed bacterial suspensions also significantly inhibited CHG activity. Additionally, we found that pig corneas also reduced CHG activity. In contrast, dry eye drops and their major component, propylene glycol, which is commonly used as eyewash material, did not have an impact on CHG activity. Our results demonstrate the effect of ocular microenvironmental factors on CHG activity and suggest that these factors may play a role in the development of amoeba resistance to CHG and treatment failure.

Homeostasis of cellular amino acids in Acanthamoeba castellanii exposed to different media under amoeba-bacteria coculture conditions.

BACKGROUND: Acanthamoeba castellanii is a free-living protist that feeds on diverse bacteria. A. castellanii has frequently been utilized in studies on microbial interactions. Grazing bacteria also exhibit diverse effects on the physiological characteristics of amoebae, such as their growth, encystation, and cytotoxicity. Since the composition of amoebae amino acids is closely related to cellular activities, it can indicate the overall responses of A. castellanii to various stimuli. METHOD: A. castellanii was exposed to different culture conditions in low-nutrient medium with heat-killed DH5α to clarify their effects. A targeted metabolomic technique was utilized to evaluate the concentration of cellular amino acids. The amino acid composition and pathways were analyzed by two web-based tools: MetaboAnalyst and Pathview. Then, long-term exposure to A. castellanii was investigated through in silico and in vitro methods to elucidate the homeostasis of amino acids and the growth of A. castellanii. RESULTS: Under short-term exposure, all kinds of amino acids were enriched in all exposed groups. In contrast to the presence of heat-killed bacteria, the medium exhibited obvious effects on the amino acid composition of A. castellanii. After long-term exposure, the amino acid composition was more similar to that of the control group. A. castellanii may achieve amino acid homeostasis through pathways related to alanine, aspartate, citrulline, and serine. DISCUSSION: Under short-term exposure, compared to the presence of bacteria, the type of medium exerted a more powerful effect on the amino acid composition of the amoeba. Previous studies focused on the interaction of the amoeba and bacteria with effective secretion systems and effectors. This may have caused the effects of low-nutrient environments to be overlooked. CONCLUSION: When A. castellanii was stimulated in the coculture system through various methods, such as the presence of bacteria and a low-nutrient environment, it accumulated intracellular amino acids within a short period. However, different stimulations correspond to different amino acid compositions. After long-term exposure, A. castellanii achieved an amino acid equilibrium by downregulating the biosynthesis of several amino acids.

Effects of Electrode Materials on Electron Transport for Single-Molecule Junctions.

The contact at the molecule-electrode interface is a key component for a range of molecule-based devices involving electron transport. An electrode-molecule-electrode configuration is a prototypical testbed for quantitatively studying the underlying physical chemistry. Rather than the molecular side of the interface, this review focuses on examples of electrode materials in the literature. The basic concepts and relevant experimental techniques are introduced.

Increased Surface Density of States at the Fermi Level for Electron Transport Across Single-Molecule Junctions.

Fermi's golden rule, a remarkable concept for the transition probability involving continuous states, is applicable to the interfacial electron-transporting efficiency via correlation with the surface density of states (SDOS). Yet, this concept has not been reported to tailor single-molecule junctions where gold is an overwhelmingly popular electrode material due to its superior amenability in regenerating molecular junctions. At the Fermi level, however, the SDOS of gold is small due to its fully filled d-shell. To increase the electron-transport efficiency, herein, gold electrodes are modified by a monolayer of platinum or palladium that bears partially filled d-shells and exhibits significant SDOS at the Fermi energy. An increase by 2-30 fold is found for single-molecule conductance of α,ω-hexanes bridged via common headgroups. The improved junction conductance is attributed to the electrode self-energy which involves a stronger coupling with the molecule and a larger SDOS participated by d-electrons at the electrode-molecule interfaces.

Tuning surface d bands with bimetallic electrodes to facilitate electron transport across molecular junctions.

Understanding chemical bonding and conductivity at the electrode-molecule interface is key for the operation of single-molecule junctions. Here we apply the d-band theory that describes interfacial interactions between adsorbates and transition metal surfaces to study electron transport across these devices. We realized bimetallic Au electrodes modified with a monoatomic Ag adlayer to connect α,ω-alkanoic acids (HO2C(CH2)nCO2H). The force required to break the molecule-electrode binding and the contact conductance Gn=0 are 1.1 nN and 0.29 G0 (the conductance quantum, 1 G0 = 2e2/h ≈ 77.5 µS), which makes these junctions, respectively, 1.3-1.8 times stronger and 40-60-fold more conductive than junctions with bare Au or Ag electrodes. A similar performance was found for Au electrodes modified by Cu monolayers. By integrating the Newns-Anderson model with the Hammer-Nørskov d-band model, we explain how the surface d bands strengthen the adsorption and promote interfacial electron transport, which provides an alternative avenue for the optimization of molecular electronic devices.

Interrelationships between the extracellular matrix and the immune microenvironment that govern epithelial tumour progression.

Solid tumours are composed of cancer cells characterised by genetic mutations that underpin the disease, but also contain a suite of genetically normal cells and the extracellular matrix (ECM). These two latter components are constituents of the tumour microenvironment (TME), and are key determinants of tumour biology and thereby the outcomes for patients. The tumour ECM has been the subject of intense research over the past two decades, revealing key biochemical and mechanobiological principles that underpin its role in tumour cell proliferation and survival. However, the ECM also strongly influences the genetically normal immune cells within the microenvironment, regulating not only their proliferation and survival, but also their differentiation and access to tumour cells. Here we review recent advances in our knowledge of how the ECM regulates the tumour immune microenvironment and vice versa, comparing normal skin wound healing to the pathological condition of tumour progression.

Fluorescent aptasensor based on conformational switch-induced hybridization for facile detection of ß-amyloid oligomers.

Aß oligomers (AßO) are a dominant biomarker for early Alzheimer's disease diagnosis. A fluorescent aptasensor coupled with conformational switch-induced hybridization was established to detect AßO. The fluorescent aptasensor is based on the interaction of fluorophore-labeled AßO-specific aptamer (FAM-Apt) against its partly complementary DNA sequence on the surface of magnetic beads (cDNA-MBs). Once the FAM-Apt binds to AßO, the conformational switch of FAM-Apt increases the tendency to be captured by cDNA-MBs. This causes a descending fluorescence of supernatant, which can be utilized to determine the levels of AßO. Thus, the base-pair matching above 12 between FAM-Apt and cDNA-MBs with increasing hybridizing free energies reached the ascending fluorescent signal equilibrium. The optimized aptasensor showed linearity from 1.7 ng mL-1 to 85.1 (R = 0.9977) with good recoveries (79.27-109.17%) in plasma. Furthermore, the established aptasensor possesses rational selectivity in the presence of monomeric Aß, fibrotic Aß, and interferences. Therefore, the developed aptasensor is capable of quantifying AßO in human plasma and possesses the potential to apply in clinical cases.

Energy Efficiency of Inference Algorithms for Clinical Laboratory Data Sets: Green Artificial Intelligence Study.

BACKGROUND: The use of artificial intelligence (AI) in the medical domain has attracted considerable research interest. Inference applications in the medical domain require energy-efficient AI models. In contrast to other types of data in visual AI, data from medical laboratories usually comprise features with strong signals. Numerous energy optimization techniques have been developed to relieve the burden on the hardware required to deploy a complex learning model. However, the energy efficiency levels of different AI models used for medical applications have not been studied. OBJECTIVE: The aim of this study was to explore and compare the energy efficiency levels of commonly used machine learning algorithms-logistic regression (LR), k-nearest neighbor, support vector machine, random forest (RF), and extreme gradient boosting (XGB) algorithms, as well as four different variants of neural network (NN) algorithms-when applied to clinical laboratory datasets. METHODS: We applied the aforementioned algorithms to two distinct clinical laboratory data sets: a mass spectrometry data set regarding Staphylococcus aureus for predicting methicillin resistance (3338 cases; 268 features) and a urinalysis data set for predicting Trichomonas vaginalis infection (839,164 cases; 9 features). We compared the performance of the nine inference algorithms in terms of accuracy, area under the receiver operating characteristic curve (AUROC), time consumption, and power consumption. The time and power consumption levels were determined using performance counter data from Intel Power Gadget 3.5. RESULTS: The experimental results indicated that the RF and XGB algorithms achieved the two highest AUROC values for both data sets (84.7% and 83.9%, respectively, for the mass spectrometry data set; 91.1% and 91.4%, respectively, for the urinalysis data set). The XGB and LR algorithms exhibited the shortest inference time for both data sets (0.47 milliseconds for both in the mass spectrometry data set; 0.39 and 0.47 milliseconds, respectively, for the urinalysis data set). Compared with the RF algorithm, the XGB and LR algorithms exhibited a 45% and 53%-60% reduction in inference time for the mass spectrometry and urinalysis data sets, respectively. In terms of energy efficiency, the XGB algorithm exhibited the lowest power consumption for the mass spectrometry data set (9.42 Watts) and the LR algorithm exhibited the lowest power consumption for the urinalysis data set (9.98 Watts). Compared with a five-hidden-layer NN, the XGB and LR algorithms achieved 16%-24% and 9%-13% lower power consumption levels for the mass spectrometry and urinalysis data sets, respectively. In all experiments, the XGB algorithm exhibited the best performance in terms of accuracy, run time, and energy efficiency. CONCLUSIONS: The XGB algorithm achieved balanced performance levels in terms of AUROC, run time, and energy efficiency for the two clinical laboratory data sets. Considering the energy constraints in real-world scenarios, the XGB algorithm is ideal for medical AI applications.

Spontaneous Assembly and Three-Dimensional Stacking of Antiaromatic 5,15-Dioxaporphyrin on HOPG.

Antiaromatic compounds have recently received considerable attention because of their novel properties such as narrow HOMO-LUMO gaps and facile formation of mutual stacking. Here, the spontaneous assembly of antiaromatic meso-2-thienyl-substituted 5,15-dioxaporphyrin (DOP-1) is scrutinized at the liquid-solid interface by scanning tunneling microscopy (STM). Polymorphism in monolayers characterized by the orthogonal and parallel assemblies is found at the low concentration of 0.05 mM. The parallel assembly is more stable and dominantly formed at higher concentrations. Aggregation was observed at concentrations >0.2 mM, and the STM images of the aggregates implied the formation of stacked layers. The intrinsic electronic structures of the mutually stacked bilayer generated by applying an electric pulse to the monolayer were probed by scanning tunneling spectroscopy to reveal the narrowing of the HOMO-LUMO gap by about 20 % compared with the monolayer, thus suggesting significant molecular orbital interactions.

The Role of Autophagy in Anti-Cancer and Health Promoting Effects of Cordycepin.

Cordycepin is an adenosine derivative isolated from Cordyceps sinensis, which has been used as an herbal complementary and alternative medicine with various biological activities. The general anti-cancer mechanisms of cordycepin are regulated by the adenosine A3 receptor, epidermal growth factor receptor (EGFR), mitogen-activated protein kinases (MAPKs), and glycogen synthase kinase (GSK)-3ß, leading to cell cycle arrest or apoptosis. Notably, cordycepin also induces autophagy to trigger cell death, inhibits tumor metastasis, and modulates the immune system. Since the dysregulation of autophagy is associated with cancers and neuron, immune, and kidney diseases, cordycepin is considered an alternative treatment because of the involvement of cordycepin in autophagic signaling. However, the profound mechanism of autophagy induction by cordycepin has never been reviewed in detail. Therefore, in this article, we reviewed the anti-cancer and health-promoting effects of cordycepin in the neurons, kidneys, and the immune system through diverse mechanisms, including autophagy induction. We also suggest that formulation changes for cordycepin could enhance its bioactivity and bioavailability and lower its toxicity for future applications. A comprehensive understanding of the autophagy mechanism would provide novel mechanistic insight into the anti-cancer and health-promoting effects of cordycepin.

Template-Assisted Proximity for Oligomerization of Fullerenes.

Demonstrated herein is an unprecedented porous template-assisted reaction at the solid-liquid interface involving bond formation, which is typically collision-driven and occurs in the solution and gas phases. The template is a TMA (trimesic acid) monolayer with two-dimensional pores that host fullerenes, which otherwise exhibit an insignificant affinity to an undecorated graphite substrate. The confinement of C84 units in the TMA pores formulates a proximity that is ideal for bond formation. The oligomerization of C84 is triggered by an electric pulse via a scanning tunneling microscope tip. The spacing between C84 moieties becomes 1.4 nm, which is larger than the edge-to-edge diameter of 1.1-1.2 nm of C84 due to the formation of intermolecular single bonds. In addition, the characteristic mass-to-charge ratios of dimers and trimers are observed by mass spectrometry. The experimental findings shed light on the active role of spatially tailored templates in facilitating the chemical activity of guest molecules.

The Cyclic Hydrogen-Bonded 6-Azaindole Trimer and its Prominent Excited-State Triple-Proton-Transfer Reaction.

The compound 6-azaindole undergoes self-assembly by formation of N(1)-H⋅⋅⋅N(6) hydrogen bonds (H bonds), forming a cyclic, triply H-bonded trimer. The formation phenomenon is visualized by scanning tunneling microscopy. Remarkably, the H-bonded trimer undergoes excited-state triple proton transfer (ESTPT), resulting in a proton-transfer tautomer emission maximized at 435 nm (325 nm of the normal emission) in cyclohexane. Computational approaches affirm the thermodynamically favorable H-bonded trimer formation and the associated ESTPT reaction. Thus, nearly half a century after Michael Kasha discovered the double H-bonded dimer of 7-azaindole and its associated excited-state double-proton-transfer reaction, the triply H-bonded trimer formation of 6-azaindole and its ESTPT reaction are demonstrated.

MicroRNA-205 targets tight junction-related proteins during urothelial cellular differentiation.

The mammalian bladder urothelium classified as basal, intermediate, and terminally differentiated umbrella cells offers one of the most effective permeability barrier functions known to exist in nature because of the formation of apical uroplakin plaques and tight junctions. To improve our understanding of urothelial differentiation, we analyzed the microRNA (miRNA) expression profiles of mouse urinary tissues and by TaqMan miRNA analysis of microdissected urothelial layers and in situ miRNA-specific hybridization to determine the dependence of these miRNAs on the differentiation stage. Our in situ hybridization studies revealed that miR-205 was enriched in the undifferentiated basal and intermediate cell layers. We then used a quantitative proteomics approach to identify miR-205 target genes in primary cultured urothelial cells subjected to antagomir-mediated knockdown of specific miRNAs. Twenty-four genes were reproducibly regulated by miR-205; eleven of them were annotated as cell junction- and tight junction-related molecules. Western blot analysis demonstrated that antagomir-induced silencing of miR-205 in primary cultured urothelial cells elevated the expression levels of Tjp1, Cgnl1, and Cdc42. Ectopic expression of miR-205 in MDCK cells inhibited the expression of tight junction proteins and the formation of tight junctions. miR-205- knockdown urothelial cells showed alterations in keratin synthesis and increases of uroplakin Ia and Ib, which are the urothelial differentiation products. These results suggest that miR-205 may contribute a role in regulation of urothelial differentiation by modulating the expression of tight junction-related molecules.

Benefits of Imperfect Conflict Resolution Advisory Aids for Future Air Traffic Control.

OBJECTIVE: The aim of this study was to examine the human-automation interaction issues and the interacting factors in the context of conflict detection and resolution advisory (CRA) systems. BACKGROUND: The issues of imperfect automation in air traffic control (ATC) have been well documented in previous studies, particularly in conflict-alerting systems. The extent to which the prior findings can be applied to an integrated conflict detection and resolution system in future ATC remains unknown. METHOD: Twenty-four participants were evenly divided into two groups corresponding to a medium- and a high-traffic density condition, respectively. In each traffic density condition, participants were instructed to perform simulated ATC tasks under four automation conditions, including reliable, unreliable with short time allowance to secondary conflict (TAS), unreliable with long TAS, and manual conditions. Dependent variables accounted for conflict resolution performance, workload, situation awareness, and trust in and dependence on the CRA aid, respectively. RESULTS: Imposing the CRA automation did increase performance and reduce workload as compared with manual performance. The CRA aid did not decrease situation awareness. The benefits of the CRA aid were manifest even when it was imperfectly reliable and were apparent across traffic loads. In the unreliable blocks, trust in the CRA aid was degraded but dependence was not influenced, yet the performance was not adversely affected. CONCLUSION: The use of CRA aid would benefit ATC operations across traffic densities. APPLICATION: CRA aid offers benefits across traffic densities, regardless of its imperfection, as long as its reliability level is set above the threshold of assistance, suggesting its application for future ATC.

Tuning molecule-substrate coupling via deposition of metal adatoms.

Organic-inorganic hybrids constitute an important class of functional materials. The fundamentals at the molecular levels are, however, relatively unexplored. PTCDA (perylene-3,4,9,10-tetracarboxylic dianhydride) is a colorant and extensively applied in organic-based optoelectronic devices. PTCDA/Cu(111) and Fe-PTCDA/Cu(111) metal-organic hybrid monolayers are studied by low temperature scanning tunneling microscopy and spectroscopy (STS) and density functional theory (DFT). The former exhibits Moiré pattern-modulated molecular density of states while the latter adapts a commensurate adlattice. Both imaging and spectroscopic results suggest a strong hybridization between PTCDA molecules and Cu(111) substrate. Weak PTCDA-Cu(111) coupling can be obtained by the introduction of Fe adatoms. Compared to PTCDA/Cu(111), STS spectra of Fe-PTCDA/Cu(111) exhibit a higher energy and sharper features of the frontier orbitals. Together with the DFT results, we found that the PTCDA-Cu(111) coupling is attenuated by the presence of Fe adatoms and Fe-PTCDA coordination.

Gastrointestinal metastasis from primary sarcomatoid carcinoma of the lung: a case report and review of the literature.

Gastrointestinal metastases in lung cancer are extremely rare. The report presents a rare case of primary lung sarcomatoid carcinoma with both gastric and colonic metastases, and reviews the literature about endoscopic presentation of colonic metastases.

Lifting motion simulation using a hybrid approach.

In this study, a hybrid dynamic model for lifting motion simulation is presented. The human body is represented by a two-dimensional (2D) five-segment model. The lifting motions are predicted by solving a nonlinear optimisation problem, the objective function of which is defined based on a minimal-effort performance criterion. In the optimisation procedure, the joint angular velocities are bounded by time-functional constraints that are determined by actual motions. Symmetric lifting motions performed by younger and older adults under varied task conditions were simulated. Comparisons between the simulation results and actual motion data were made for model evaluation. The results showed that the mean and median joint angle errors were less than 10°, which suggests the proposed model is able to accurately simulate 2D lifting motions. The proposed model is also comparable with the existing motion simulation models in terms of the prediction accuracy. Strengths and limitations of this hybrid model are discussed. Practitioner Summary: Human motion simulation is a useful tool in assessing the risks of occupational injuries. Lifting motions are associated with low-back pain. A hybrid model for lifting motion simulation was constructed. The model was able to accurately simulate 2D lifting motions in varied task scenarios for younger and older subjects.

Human factors assessment of conflict resolution aid reliability and time pressure in future air traffic control.

Though it has been reported that air traffic controllers' (ATCos') performance improves with the aid of a conflict resolution aid (CRA), the effects of imperfect automation on CRA are so far unknown. The main objective of this study was to examine the effects of imperfect automation on conflict resolution. Twelve students with ATC knowledge were instructed to complete ATC tasks in four CRA conditions including reliable, unreliable and high time pressure, unreliable and low time pressure, and manual conditions. Participants were able to resolve the designated conflicts more accurately and faster in the reliable versus unreliable CRA conditions. When comparing the unreliable CRA and manual conditions, unreliable CRA led to better conflict resolution performance and higher situation awareness. Surprisingly, high time pressure triggered better conflict resolution performance as compared to the low time pressure condition. The findings from the present study highlight the importance of CRA in future ATC operations. Practitioner Summary: Conflict resolution aid (CRA) is a proposed automation decision aid in air traffic control (ATC). It was found in the present study that CRA was able to promote air traffic controllers' performance even when it was not perfectly reliable. These findings highlight the importance of CRA in future ATC operations.

Force Spectroscopy of Metal-Crown Ether Multivalency: Effect of Local Environments on Energy Landscape and Sensing Kinetics.

Sandwich complexation involving alkali or alkaline-earth metals, multivalency, and effects associated with local environments is widely encountered in biological and synthetic systems yet the mechanic properties remain unexplored. Herein, AFM (atomic force microscopy)-based single-molecule force spectroscopy is employed to investigate a classical model of M(n+)[15C5]2, a metal cation hosted jointly by two 15-crown-5 moieties immobilized on both the substrate and the AFM tip. Factors reportedly promoting the recognition performance are examined. The rupture force required to break apart M(n+)[15C5]2 is found to be in the order of tens of pico-Newton, e.g., f(ß)=31 pN for K(+)[15C5]2. The presence of a second functional group, carboxylate, confers K(+)[15C5]2 with a longer lifetime (from 13 to 16 ms), faster association (from 0.4 to 1.3×10(6) M(-1) s(-1)), and slower dissociation (from 77 to 62 s(-1)). The effect of local environments is significant on association yet less critical on dissociation pathways.

Energy-Level Alignment for Single-Molecule Conductance of Extended Metal-Atom Chains.

The use of single-molecule junctions for various functions constitutes a central goal of molecular electronics. The functional features and the efficiency of electron transport are dictated by the degree of energy-level alignment (ELA), that is, the offset potential between the electrode Fermi level and the frontier molecular orbitals. Examples manifesting ELA are rare owing to experimental challenges and the large energy barriers of typical model compounds. In this work, single-molecule junctions of organometallic compounds with five metal centers joined in a collinear fashion were analyzed. The single-molecule i-V scans could be conducted in a reliable manner, and the EFMO levels were electrochemically accessible. When the electrode Fermi level (EF ) is close to the frontier orbitals (EFMO ) of the bridging molecule, larger conductance was observed. The smaller |EF -EFMO | gap was also derived quantitatively, unambiguously confirming the ELA. The mechanism is described in terms of a two-level model involving co-tunneling and sequential tunneling processes.