Forsythia velutina Nakai extract: A promising therapeutic option for atopic dermatitis through multiple cell type modulation.

BACKGROUND: Atopic dermatitis (AD) is a complex condition characterized by impaired epithelial barriers and dysregulated immune cells. In this study, we demonstrated Forsythia velutina Nakai extract (FVE) simultaneously inhibits basophils, macrophages, keratinocytes, and T cells that are closely interrelated in AD development. METHODS: We analyzed the effect of FVE on nitric oxide and reactive oxygen species (ROS) production in macrophages, basophil degranulation, T cell activation, and tight junctions in damaged keratinocytes. Expression of cell-type-specific inflammatory mediators was analyzed, and the underlying signaling pathways for anti-inflammatory effects of FVE were investigated. The anti-inflammatory effects of FVE were validated using a DNCB-induced mouse model of AD. Anti-inflammatory activity of compounds isolated from FVE was validated in each immune cell type. RESULTS: FVE downregulated the expression of inflammatory mediators and ROS production in macrophages through TLR4 and NRF2 pathways modulation. It significantly reduced basophil degranulation and expression of type 2 (T2) and pro-inflammatory cytokines by perturbing FcεRI signaling. Forsythia velutina Nakai extract also robustly inhibited the expression of T2 cytokines in activated T cells. Furthermore, FVE upregulated the expression of tight junction molecules in damaged keratinocytes and downregulated leukocyte attractants, as well as IL-33, an inducer of T2 inflammation. In the AD mouse model, FVE showed superior improvement in inflammatory cell infiltration and skin structure integrity compared to dexamethasone. Dimatairesinol, a lignan dimer, was identified as the most potent anti-inflammatory FVE compound. CONCLUSION: Forsythia velutina Nakai extract and its constituent compounds demonstrate promising efficacy as a therapeutic option for prolonged AD treatment by independently inhibiting various cell types associated with AD and disrupting the deleterious link between them.

Chemical constituents isolated from Actinidia polygama and their α-glucosidase inhibitory activity and insulin secretion effect.

Actinidia polygama has been used as a traditional medicine for treating various diseases. In the present study, 13 compounds, including three new monoterpenoids (1-3), were isolated from the leaves of A. polygama to investigate the bioactive constituents of the plant. The structures were characterized by analyzing spectroscopic and chiroptical data. These compounds were preliminarily screened for their ability to increase insulin secretion levels after glucose stimulation. Of these, 3-O-coumaroylmaslinic acid (4) and jacoumaric acid (5) showed activity. In further biological studies, these compounds exhibited increased glucose-stimulated insulin secretion (GSIS) activity without cytotoxicity in rat INS-1 pancreatic ß-cells as well as α-glucosidase inhibitory activity. Furthermore, both compounds increased insulin receptor substrate-2 (IRS-2), phosphatidylinositol 3-kinase (PI3K), protein kinase B (Akt), pancreatic and duodenal homeobox-1 (PDX-1), and peroxisome proliferator-activated receptor-γ (PPAR-γ) expression. Hence, these compounds may be developed as potential antidiabetic agents.

Feedback-controlled solute transport through chemo-responsive polymer membranes.

Polymer membranes are typically assumed to be inert and nonresponsive to the flux and density of the permeating particles in transport processes. Here, we theoretically study the consequences of membrane responsiveness and feedback on the steady-state force-flux relations and membrane permeability using a nonlinear-feedback solution-diffusion model of transport through a slab-like membrane. Therein, the solute concentration inside the membrane depends on the bulk concentration, c0, the driving force, f, and the polymer volume fraction, ϕ. In our model, the solute accumulation in the membrane causes a sigmoidal volume phase transition of the polymer, changing its permeability, which, in return, affects the membrane's solute uptake. This feedback leads to nonlinear force-flux relations, j(f), which we quantify in terms of the system's differential permeability, Psys Δ∝dj/df. We find that the membrane feedback can increase or decrease the solute flux by orders of magnitude, triggered by a small change in the driving force and largely tunable by attractive vs repulsive solute-membrane interactions. Moreover, controlling the inputs, c0 and f, can lead to the steady-state bistability of ϕ and hysteresis in the force-flux relations. This work advocates that the fine-tuning of the membrane's chemo-responsiveness will enhance the nonlinear transport control features, providing great potential for future (self-)regulating membrane devices.

Proton-transfer spectroscopy beyond the normal-mode scenario.

A stochastic theory is developed to predict the spectral signature of proton-transfer processes and is applied to infrared spectra computed from ab initio molecular-dynamics simulations of a single H5O2 + cation. By constraining the oxygen atoms to a fixed distance, this system serves as a tunable model for general proton-transfer processes with variable barrier height. Three spectral contributions at distinct frequencies are identified and analytically predicted: the quasi-harmonic motion around the most probable configuration, amenable to normal-mode analysis, the contribution due to transfer paths when the proton moves over the barrier, and a shoulder for low frequencies stemming from the stochastic transfer-waiting-time distribution; the latter two contributions are not captured by normal-mode analysis but exclusively reported on the proton-transfer kinetics. In accordance with reaction rate theory, the transfer-waiting-contribution frequency depends inversely exponentially on the barrier height, whereas the transfer-path-contribution frequency is rather insensitive to the barrier height.

Verification of Tensile Force Estimation Method for Temporary Steel Rods of FCM Bridges Based on Area of Magnetic Hysteresis Curve Using Embedded Elasto-Magnetic Sensor.

The free cantilever method (FCM) is a bridge construction method in which the left and right segments are joined in sequence from a pier without using a bottom strut. To support the imbalance of the left and right moments during construction, temporary steel rods, upon which tensile force is applied that cannot be managed after construction, are embedded in the pier. If there is an excessive loss of tensile force applied to the steel rods, the segments can collapse owing to the unbalanced moment, which may cause personal and property damage. Therefore, it is essential to monitor the tensile force in the temporary steel rods to prevent such accidents. In this study, a tensile force estimation method for the temporary steel rods of an FCM bridge using embedded Elasto-Magnetic (EM) sensors was proposed. After the tensile force was applied to the steel rods, the change in tensile force was monitored according to the changing area of a magnetic hysteresis curve, as measured by the embedded EM sensors. To verify the field applicability of the proposed method, the EM sensors were installed in an FCM bridge pier under construction. The three sensors were installed in conjunction with a sheath tube, and the magnetic hysteresis curve was measured over nine months. Temperature data from the measurement period were used to compensate for the error due to daily temperature fluctuations. The estimated tensile force was consistent with an error range of ±4% when compared with the reference value measured by the load cell. Based on the results of this experiment, the applicability of the proposed method was demonstrated.

Polymer brush-induced depletion interactions and clustering of membrane proteins.

We investigate the effect of mobile polymer brushes on proteins embedded in biological membranes by employing both Asakura-Oosawa type of theoretical model and coarse-grained molecular dynamics simulations. The brush polymer-induced depletion attraction between proteins changes non-monotonically with the size of brush. The depletion interaction, which is determined by the ratio of the protein size to the grafting distance between brush polymers, increases linearly with the brush size as long as the polymer brush height is shorter than the protein size. When the brush height exceeds the protein size, however, the depletion attraction among proteins is slightly reduced. We also explore the possibility of the brush polymer-induced assembly of a large protein cluster, which can be related to one of many molecular mechanisms underlying recent experimental observations of integrin nanocluster formation and signaling.

Tuning the permeability of regular polymeric networks by the cross-link ratio.

The amount of cross-linking in the design of polymer materials is a key parameter for the modification of numerous physical properties, importantly, the permeability to molecular solutes. We consider networks with a diamond-like architecture and different cross-link ratios, concurring with a wide range of the polymer volume fraction. We particularly focus on the effect and the competition of two independent component-specific solute-polymer interactions, i.e., we distinguish between chain-monomers and cross-linkers, which individually act on the solutes and are altered to cover attractive and repulsive regimes. For this purpose, we employ coarse-grained, Langevin computer simulations to study how the cross-link ratio of polymer networks controls the solute partitioning, diffusion, and permeability. We observe different qualitative behaviors as a function of the cross-link ratio and interaction strengths. The permeability can be tuned ranging over two orders of magnitude relative to the reference bulk permeability. Finally, we provide scaling theories for the partitioning and diffusion that explicitly account for the component-specific interactions as well as the cross-link ratio and the polymer volume fraction. These are in overall good agreement with the simulation results and grant insight into the underlying physics, rationalizing how the cross-link ratio can be exploited to tune the solute permeability of polymeric networks.

Tuning the selective permeability of polydisperse polymer networks.

We study the permeability and selectivity ('permselectivity') of model membranes made of polydisperse polymer networks for molecular penetrant transport, using coarse-grained, implicit-solvent computer simulations. In our work, permeability P is determined on the linear-response level using the solution-diffusion model, P = KDin, i.e., by calculating the equilibrium penetrant partition ratio K and penetrant diffusivity Din inside the membrane. We vary two key parameters, namely the network-network interaction, which controls the degree of swelling and collapse of the network, and the network-penetrant interaction, which tunes the selective penetrant uptake and microscopic energy landscape for diffusive transport. We find that the partitioning K covers four orders of magnitude and is a non-monotonic function of the parameters, well interpreted by a second-order virial expansion of the free energy of transferring one penetrant from a reservoir into the membrane. Moreover, we find that the penetrant diffusivity Din in the polydisperse networks, in contrast to highly ordered membrane structures, exhibits relatively simple exponential decays. We propose a semi-empirical scaling law for the penetrant diffusion that describes the simulation data for a wide range of densities and interaction parameters. The resulting permeability P turns out to follow the qualitative behavior (including maximization and minimization) of partitioning. However, partitioning and diffusion are typically anti-correlated, yielding large quantitative cancellations, controlled and fine-tuned by the network density and interactions, as rationalized by our scaling laws. We finally demonstrate that even small changes of network-penetrant interactions, e.g., by half a kBT, modify the permselectivity by almost one order of magnitude.

Tuning the Permeability of Dense Membranes by Shaping Nanoscale Potentials.

Permeability is one of the most fundamental transport properties in soft matter physics, material engineering, and nanofluidics. Here, we report by means of Langevin simulations of ideal penetrants in a nanoscale membrane made of a fixed lattice of attractive interaction sites, how the permeability can be massively tuned, even minimized or maximized, by tailoring the potential energy landscape for the diffusing penetrants, depending on the membrane attraction, topology, and density. Supported by limiting scaling theories we demonstrate that the observed nonmonotonic behavior and the occurrence of extreme values of the permeability is far from trivial and triggered by a strong anticorrelation and substantial (orders of magnitude) cancellation between penetrant partitioning and diffusivity, especially within dense and highly attractive membranes.

Detection of Helicobacter pylori with clarithromycin resistance-associated mutations using peptide nucleic acid probe-based melting point analysis.

BACKGROUND: Detection of Helicobacter pylori in gastric biopsy is important for appropriate treatment and prevention of gastric carcinoma and lymphoma. A novel peptide nucleic acid probe (PNA)-based real-time polymerase chain reaction (PCR) method was developed for detection of H pylori and A2142G/A2143G mutation of the 23S rRNA gene, which is associated with clarithromycin resistance. METHODS: To evaluate the performance of the PNA probe-based PCR method, a total of 409 gastric biopsy samples were analyzed by PNA probe-based PCR and compared with other H pylori detection methods, including hematoxylin and eosin (HE) and Warthin-Starry (WS) staining, immunohistochemistry (IHC). A2142G/A2143G mutation of the 23S rRNA gene was tested by dual priming oligonucleotide (DPO)-based PCR and Sanger sequencing to evaluate PNA probe-based PCR. RESULTS: Among 271 cases that were positive for H pylori on IHC which was considered as a standard method, 264 cases (97.4%) and 259 cases (95.6%) were positively detected by HE/WS and PNA probe-based qPCR, respectively. Of 100 H pylori-positive patients tested by IHC, H pylori was detected in 93 cases (93.0%) by PNA probe-based PCR, 86 cases (86.0%) by DPO-based PCR, and 93 cases (93.0%) by conventional PCR. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of PNA probe-based qPCR were 93.0%, 94.9%, 93.9%, 94.9%, and 93.0%, respectively, which were all higher than those of DPO-based PCR. When Sanger sequencing was determined as a standard method to detect A2142G/A2143G mutations, the sensitivity of the PNA- and DPO-based methods was 100% and 94.4%, respectively, and the specificity was 100% for both methods. CONCLUSION: PNA probe-based qPCR is an appropriate method for detecting H pylori and the clarithromycin resistance-associated mutation type.

Survivin is a novel transcription regulator of KIT and is downregulated by miRNA-494 in gastrointestinal stromal tumors.

Gain-of-function mutations of KIT are pathognomonic in sporadic gastrointestinal stromal tumors (GISTs). Several microRNAs have been shown to be dysregulated in GISTs and impact KIT expression. Little is known though on KIT-independent targets of KIT-regulating mRNAs. We sought to investigate how miR-494 inhibits GIST proliferation and to identify novel target gene. We used microarray-based gene expression analyses to identify pathways and target genes affected by miR-494. The expressional relationship between survivin and miR-494 was determined in 35 GIST tissues. Cell proliferation assay, FACS analysis, colony formation assay, promoter assays and chromatin immunoprecipitation (ChiP) were performed to clarify the roles of survivin in GIST progression. Gene expression microarray analysis revealed that miR-494 inhibited GISTs by affecting multiple genes in the cell cycle pathway. Survivin (BIRC5) was a key target of miR-494, and its expression showed an inverse correlation with miR-494 expression in 35 GIST tissues (Pearson's correlation coefficient, r = -0.418, p = 0.012). Downregulation of survivin inhibited proliferation and colony formation, and resulted in cell cycle alteration. Induced survivin overexpression relieved miR-494-mediated inhibition of GIST progression. Targeting PI3K effectively suppressed proliferation of GISTs with downregulation of survivin. Survivin also regulated KIT expression at the transcription level. Immunohistochemical analysis using 113 GISTs revealed that survivin expression was significantly correlated with overall survival of GIST patients (p = 0.004). Our findings indicated that miR-494 synergistically suppressed GISTs by concomitantly targeting survivin and KIT.

Microsatellite instability test using peptide nucleic acid probe-mediated melting point analysis: a comparison study.

BACKGROUND: Analysis of high microsatellite instability (MSI-H) phenotype in colorectal carcinoma (CRC) is important for evaluating prognosis and choosing a proper adjuvant therapy. Although the conventional MSI analysis methods such as polymerase chain reaction (PCR) fragment analysis and immunohistochemistry (IHC) show high specificity and sensitivity, there are substantial barriers to their use. METHODS: In this study, we analyzed the MSI detection performance of three molecular tests and IHC. For the molecular tests, we included a recently developed peptide nucleic acid probe (PNA)-mediated real-time PCR-based method using five quasi-monomorphic mononucleotide repeat markers (PNA method) and two conventional PCR fragment analysis methods using NCI markers (NCI method) or five quasi-monomorphic mononucleotide repeat markers (MNR method). IHC analysis was performed with four mismatch repair proteins. The performance of each method was validated in 166 CRC patient samples, which consisted of 76 MSI-H and 90 microsatellite stable (MSS) CRCs previously diagnosed by NCI method. RESULTS: Of the 166 CRCs, 76 MSI-H and 90 MSS CRCs were determined by PNA method. On the other hand, 75 MSI-H and 91 MSS CRCs were commonly determined by IHC and MNR methods. Based on the originally diagnosed MSI status, PNA showed 100% sensitivity and 100% specificity while IHC and MNR showed 98.68% sensitivity and 100% specificity. When we analyzed the maximum sensitivity of MNR and PNA method, which used the same five markers, PNA method could detect alterations in all five mononucleotide repeat markers in samples containing down to 5% MSI-H DNAs, whereas MNR required at least 20% MSI-H DNAs to achieve the same performance. CONCLUSIONS: Based on these findings, we suggest that PNA method can be used as a practical laboratory test for the diagnosis of MSI.

Product interactions and feedback in diffusion-controlled reactions.

Steric or attractive interactions among reactants or between reactants and inert crowders can substantially influence the total rate of a diffusion-influenced reaction in the liquid phase. However, the role of the product species, which has typically different physical properties than the reactant species, has been disregarded so far. Here we study the effects of reactant-product and product-product interactions as well as asymmetric diffusion properties on the rate of diffusion-controlled reactions in the classical Smoluchowski-setup for chemical transformations at a perfect catalytic sphere. For this, we solve the diffusion equation with appropriate boundary conditions coupled by a mean-field approach on the second virial level to account for the particle interactions. We find that all particle spatial distributions and the total rate can change significantly, depending on the diffusion and interaction properties of the accumulated products. Complex competing and self-regulating (homeostatic) or self-amplifying effects are observed for the system, leading to both decrease and increase in the rates, as the presence of interacting products feeds back to the reactant flux and thus the rate with which the products are generated.

Clinicopathological characteristics of KIT and protein kinase C-δ expression in adenoid cystic carcinoma: comparison with chromophobe renal cell carcinoma and gastrointestinal stromal tumour.

AIMS: KIT overexpression is frequently observed in adenoid cystic carcinomas (AdCCs), chromophobe renal cell carcinomas (ChRCCs), and gastrointestinal stromal tumours (GISTs). Persistent KIT activation has been reported to be mediated by protein kinase C (PKC)-δ in a subset of colon cancers with wild-type KIT overexpression, and by PKC-θ in GISTs with mutant KIT overexpression. To elucidate the clinical implications of PKC-δ and PKC-θ expression in KIT-expressing tumours, we investigated the expression of KIT, PKC-δ and PKC-θ in AdCCs and ChRCCs in comparison with GISTs. METHODS AND RESULTS: KIT expression, PKC-δ expression and PKC-θ expression were analysed in whole sections from 41 AdCCs, 40 ChRCCs and 56 GISTs by immunohistochemistry. Membranous expression of KIT was found in 34 AdCCs and all ChRCCs, whereas cytoplasmic expression of KIT was found in 46 GISTs. In AdCCs, PKC-δ expression was associated with histological grade (P = 0.049), lymphovascular invasion (P = 0.004), perineural invasion (P = 0.002), and KIT positivity (P = 0.002). PKC-δ positivity was associated with shorter relapse-free survival (RFS) (P = 0.017) and a tendency for there to be shorter overall survival (OS) (P = 0.090) in patients with AdCCs. No clinicopathological associations were observed between PKC-δ and KIT expression in ChRCCs. In GISTs, PKC-θ expression was associated with higher mitotic count (P = 0.011) and high grade according to the modified National Institutes of Health criteria (P < 0.001). PKC-θ positivity was associated with shorter RFS (P = 0.016) and a tendency for there to be shorter OS (P = 0.051) in patients with GISTs. CONCLUSIONS: PKC-δ expression is associated with KIT expression and the prognosis of patients with AdCCs, suggesting that PKC-δ may be a potential therapeutic target for AdCCs.

Elasticity-based polymer sorting in active fluids: a Brownian dynamics study.

While the dynamics of polymer chains in equilibrium media is well understood by now, the polymer dynamics in active non-equilibrium environments can be very different. Here we study the dynamics of polymers in a viscous medium containing self-propelled particles in two dimensions by using Brownian dynamics simulations. We find that the polymer center of mass exhibits a superdiffusive motion at short to intermediate times and the motion turns normal at long times, but with a greatly enhanced diffusivity. Interestingly, the long time diffusivity shows a non-monotonic behavior as a function of chain length and stiffness. We analyze how the polymer conformation and the accumulation of self-propelled particles, and therefore the directed motion of the polymer, are correlated. At the point of maximal polymer diffusivity, the polymer has preferentially bent conformations maintained by the balance between the chain elasticity and the propelling force generated by the active particles. We also consider the barrier crossing dynamics of actively-driven polymers in a double-well potential. The barrier crossing times are demonstrated to have a peculiar non-monotonic dependence, related to that of the diffusivity. This effect can be potentially utilized for sorting polymers from solutions in in vitro experiments.

Selective solute adsorption and partitioning around single PNIPAM chains.

Thermoresponsive polymer architectures have become integral building blocks of 'smart' functional materials in modern applications. For a large range of developments, e.g. for drug delivery or nanocatalytic carrier systems, the selective adsorption and partitioning of molecules (ligands or reactants) inside the polymeric matrix are key processes that have to be controlled and tuned for the desired material function. In order to gain insights into the nanoscale structure and binding details in such systems, we here employ molecular dynamics simulations of the popular poly(N-isopropylacrylamide) (PNIPAM) polymer in explicit water in the presence of various representative solute types with a focus on aromatic model reactants. We study a single polymer chain and explore the influence of its elongation, stereochemistry, and temperature on the solute binding affinities. While we find that the excess adsorption generally increases with the size of the solute, the temperature-dependent affinity to the chain is highly solute specific and has a considerable dependence on the polymer elongation (i.e. polymer swelling state). We elucidate the molecular mechanisms of the selective binding in detail and eventually present how the results can be extrapolated to macroscopic partitioning of the solutes in swollen polymer architectures, such as hydrogels.

Nanoparticle filtering in charged hydrogels: Effects of particle size, charge asymmetry and salt concentration.

The understanding of particle transport mechanisms in biological and synthetic hydrogels is crucial for the development of advanced drug delivery methods. We propose a simple model for the diffusion of charged nanoparticles in cross-linked, charged hydrogels based on a cubic periodic environment and an electrostatic interaction potential of varying range and strength, encompassing attractive and repulsive scenarios. The long-time diffusive properties are investigated by use of Brownian dynamics simulations and analytical methods. A number of experimentally observed phenomena attributed to nonsteric interactions between hydrogel polymers and diffusing particle are naturally reproduced by our model. Charged particles diffuse slower than uncharged particles, regardless of the sign of the surface charge, but with a stronger hindrance effect for attractive electrostatic interactions. This is explained in terms of charged particles sticking to the polymer network in regions of strong opposite charge and their exclusion from similarly charged regions. In the case of attractive interactions between hydrogel polymers and the diffusing particle, smaller charged particles diffuse slower than larger ones. This stands in contrast to a size filtering scenario but is in agreement with experimental findings. In the case of repulsive interactions, a range of differently sized particles diffuse equally fast. We compare our model predictions with published experiments on charged particle diffusion in hydrogels and confirm that electrostatic interactions are a key factor influencing the diffusivity of charged nanoparticles and that oppositely charged gels are much more effective in slowing down a charged particle than similarly charged gels.

Barrier-induced dielectric counterion relaxation at super-low frequencies in salt-free polyelectrolyte solutions.

Based on the thermally activated diffusion of counterions over the barrier of the electrostatic binding potential, we construct a scaling theory for the slow dielectric response in dilute and semi-dilute polyelectrolyte solutions. The theory is based on an analytic evaluation of the mean-escape time of a single counterion from the surface of a polyelectrolyte chain and uses a variational expression for the electrostatic potential of a charged cylinder including counterion condensation. This mean-escape time shows a range of characteristic power-law dependencies on the polyelectrolyte length and the polyelectrolyte monomer concentration. The existence of this novel dielectric mode at super-low frequencies reflects the wide spectrum of experimental findings for the super-low-frequency dielectric relaxation mode and thereby helps to reconcile conflicting interpretations of experimental data in terms of conventional scaling laws. We also devise a scaling theory for the counterion condensation of finite-length polyelectrolyte chains at finite concentration, which allows us to include polyelectrolyte charge renormalization in dilute as well as semi-dilute solutions in a unified theoretical framework.

The mean shape of transition and first-passage paths.

Based on the one-dimensional Fokker-Planck equation in an arbitrary free energy landscape including a general inhomogeneous diffusivity profile, we analytically calculate the mean shape of transition paths and first-passage paths, where the shape of a path is defined as the kinetic profile in the plane spanned by the mean time and the position. The transition path ensemble is the collection of all paths that do not revisit the start position x(A) and that terminate when first reaching the final position x(B). In contrast, a first-passage path can revisit its start position x(A) before it terminates at x(B). Our theoretical framework employs the forward and backward Fokker-Planck equations as well as first-passage, passage, last-passage, and transition-path time distributions, for which we derive the defining integral equations. We show that the mean shape of transition paths, in other words the mean time at which the transition path ensemble visits an intermediate position x, is equivalent to the mean first-passage time of reaching the position x(A) when starting from x without ever visiting x(B). The mean shape of first-passage paths is related to the mean shape of transition paths by a constant time shift. Since for a large barrier height U, the mean first-passage time scales exponentially in U, while the mean transition path time scales linearly inversely in U, the time shift between first-passage and transition path shapes is substantial. We present explicit examples of transition path shapes for linear and harmonic potentials and illustrate our findings by trajectories obtained from Brownian dynamics simulations.

Weak temporal signals can synchronize and accelerate the transition dynamics of biopolymers under tension.

In addition to thermal noise, which is essential to promote conformational transitions in biopolymers, the cellular environment is replete with a spectrum of athermal fluctuations that are produced from a plethora of active processes. To understand the effect of athermal noise on biological processes, we studied how a small oscillatory force affects the thermally induced folding and unfolding transition of an RNA hairpin, whose response to constant tension had been investigated extensively in both theory and experiments. Strikingly, our molecular simulations performed under overdamped condition show that even at a high (low) tension that renders the hairpin (un)folding improbable, a weak external oscillatory force at a certain frequency can synchronously enhance the transition dynamics of RNA hairpin and increase the mean transition rate. Furthermore, the RNA dynamics can still discriminate a signal with resonance frequency even when the signal is mixed among other signals with nonresonant frequencies. In fact, our computational demonstration of thermally induced resonance in RNA hairpin dynamics is a direct realization of the phenomena called stochastic resonance and resonant activation. Our study, amenable to experimental tests using optical tweezers, is of great significance to the folding of biopolymers in vivo that are subject to the broad spectrum of cellular noises.