Construction of human 3D striato-nigral assembloids to recapitulate medium spiny neuronal projection defects in Huntington's disease.

The striato-nigral (Str-SN) circuit is composed of medium spiny neuronal projections that are mainly sent from the striatum to the midbrain substantial nigra (SN), which is essential for regulating motor behaviors. Dysfunction of the Str-SN circuitry may cause a series of motor disabilities that are associated with neurodegenerative disorders, such as Huntington's disease (HD). Although the etiology of HD is known as abnormally expanded CAG repeats of the huntingtin gene, treatment of HD remains tremendously challenging. One possible reason is the lack of effective HD model that resembles Str-SN circuitry deficits for pharmacological studies. Here, we first differentiated striatum-like organoids from human pluripotent stem cells (hPSCs), containing functional medium spiny neurons (MSNs). We then generated 3D Str-SN assembloids by assembling striatum-like organoids with midbrain SN-like organoids. With AAV-hSYN-GFP-mediated viral tracing, extensive MSN projections from the striatum to the SN are established, which formed synaptic connection with GABAergic neurons in SN organoids and showed the optically evoked inhibitory postsynaptic currents and electronic field potentials by labeling the striatum-like organoids with optogenetic virus. Furthermore, these Str-SN assembloids exhibited enhanced calcium activity compared to that of individual striatal organoids. Importantly, we further demonstrated the reciprocal projection defects in HD iPSC-derived assembloids, which could be ameliorated by treatment of brain-derived neurotrophic factor. Taken together, these findings suggest that Str-SN assembloids could be used for identifying MSN projection defects and could be applied as potential drug test platforms for HD.

A nanofluidic spiking synapse.

Currently, the nanofluidic synapse can only perform basic neuromorphic pulse patterns. One immediate problem that needs to be addressed to further its capability of brain-like computing is the realization of a nanofluidic spiking device. Here, we report the use of a poly(3,4-ethylenedioxythiophene) polystyrene sulfonate membrane to achieve bionic ionic current-induced spiking. In addition to the simulation of various electrical pulse patterns, our synapse could produce transmembrane ionic current-induced spiking, which is highly analogous to biological action potentials with similar phases and excitability. Moreover, the spiking properties could be modulated by ions and neurochemicals. We expect that this work could contribute to biomimetic spiking computing in solution.

Sonrotoclax overcomes BCL2 G101V mutation-induced venetoclax resistance in preclinical models of hematologic malignancy.

ABSTRACT: Venetoclax, the first-generation inhibitor of the apoptosis regulator B-cell lymphoma 2 (BCL2), disrupts the interaction between BCL2 and proapoptotic proteins, promoting the apoptosis in malignant cells. Venetoclax is the mainstay of therapy for relapsed chronic lymphocytic leukemia and is under investigation in multiple clinical trials for the treatment of various cancers. Although venetoclax treatment can result in high rates of durable remission, relapse has been widely observed, indicating the emergence of drug resistance. The G101V mutation in BCL2 is frequently observed in patients who relapsed treated with venetoclax and sufficient to confer resistance to venetoclax by interfering with compound binding. Therefore, the development of next-generation BCL2 inhibitors to overcome drug resistance is urgently needed. In this study, we discovered that sonrotoclax, a potent and selective BCL2 inhibitor, demonstrates stronger cytotoxic activity in various hematologic cancer cells and more profound tumor growth inhibition in multiple hematologic tumor models than venetoclax. Notably, sonrotoclax effectively inhibits venetoclax-resistant BCL2 variants, such as G101V. The crystal structures of wild-type BCL2/BCL2 G101V in complex with sonrotoclax revealed that sonrotoclax adopts a novel binding mode within the P2 pocket of BCL2 and could explain why sonrotoclax maintains stronger potency than venetoclax against the G101V mutant. In summary, sonrotoclax emerges as a potential second-generation BCL2 inhibitor for the treatment of hematologic malignancies with the potential to overcome BCL2 mutation-induced venetoclax resistance. Sonrotoclax is currently under investigation in multiple clinical trials.

Attractant and repellent induce opposing changes in the four-helix bundle ligand-binding domain of a bacterial chemoreceptor.

Motile bacteria navigate toward favorable conditions and away from unfavorable environments using chemotaxis. Mechanisms of sensing attractants are well understood; however, molecular aspects of how bacteria sense repellents have not been established. Here, we identified malate as a repellent recognized by the MCP2201 chemoreceptor in a bacterium Comamonas testosteroni and showed that it binds to the same site as an attractant citrate. Binding determinants for a repellent and an attractant had only minor differences, and a single amino acid substitution in the binding site inverted the response to malate from a repellent to an attractant. We found that malate and citrate affect the oligomerization state of the ligand-binding domain in opposing way. We also observed opposing effects of repellent and attractant binding on the orientation of an alpha helix connecting the sensory domain to the transmembrane helix. We propose a model to illustrate how positive and negative signals might be generated.

Intermediate-state imaging of electrical switching and quantum coupling of molybdenum disulfide monolayer.

SignificanceThin transparent semiconductors of two-dimensional materials are attractive for the practical applications in next-generation nanoelectronic and optoelectronic devices. Probing the electron states and electrical switching mechanisms of a molybdenum disulphide monolayer with atomic-scale thickness (6.5 Å) allows us to unlock the full technological potential of this nanomaterial. We introduced a plasmonic phase imaging method to uncover the underlying mechanism and detailed switching dynamics of an electrical-state switching event. This dramatic phase change can be attributed to the reversible switching of classical electromagnetic coupling and quantum coupling effects interplaying between a single metal nanoparticle and molybdenum disulphide monolayer, and the transient intermediate states during the switching event can be directly imaged by a plasmonic technique.

Unveiling the Dynamic Electrocatalytic Activity of Online Synthesized Bimetallic Nanocatalysts via Electrochemiluminescence Microscopy.

Effective bimetallic nanoelectrocatalysis demands precise control of composition, structure, and understanding catalytic mechanisms. To address these challenges, we employ a two-in-one approach, integrating online synthesis with real-time imaging of bimetallic Au@Metal core-shell nanoparticles (Au@M NPs) via electrochemiluminescence microscopy (ECLM). Within 120 s, online electrodeposition and in situ catalytic activity screening alternate. ECLM captures transient faradaic processes during potential switches, visualizes electrochemical processes in real-time, and tracks catalytic activity dynamics at the single-particle level. Analysis using ECL photon flux density eliminates size effects and yields quantitative electrocatalytic activity results. Notably, a nonlinear activity trend corresponding to the shell metal to Au surface atomic ratio is discerned, quantifying the optimal surface component ratio of Au@M NPs. This approach offers a comprehensive understanding of catalytic behavior during the deposition process with high spatiotemporal resolution, which is crucial for tailoring efficient bimetallic nanocatalysts for diverse applications.

An Ultrasensitive and Efficient microRNA Nanosensor Empowered by the CRISPR/Cas Confined in a Nanopore.

This work presents a clustered regularly interspaced short palindromic repeat (CRISPR)/Cas-nanopipette nano-electrochemistry (Cas = CRISPR-associated proteins) capable of ultrasensitive microRNA detection. Nanoconfinement of the CRISPR/Cas13a within a nanopipette leads to a high catalytic efficacy of ca. 169 times higher than that in bulk electrolyte, contributing to the amplified electrochemical responses. CRISPR/Cas13a-enabled detection of representative microRNA-25 achieves a low limit of detection down to 10 aM. Practical application of this method is further demonstrated for single-cell and real human serum detection. Its general applicability is validated by addressing microRNA-141 and the SARS-CoV-2 RNA gene fragment. This work introduces a new CRISPR/Cas-empowered nanotechnology for ultrasensitive nano-electrochemistry and bioanalysis.

Aggregation-Enabled Electrochemistry in Confined Nanopore Capable of Complementary Faradaic and Non-Faradaic Detection.

Electrochemistry that empowers innovative nanoscopic analysis has long been pursued. Here, the concept of aggregation-enabled electrochemistry (AEE) in a confined nanopore is proposed and devised by reactive oxygen species (ROS)-responsive aggregation of CdS quantum dots (QDs) within a functional nanopipette. Complementary Faradaic and non-Faradaic operations of the CdS QDs aggregate could be conducted to simultaneously induce the signal-on of the photocurrents and the signal-off of the ionic signals. Such a rationale permits the cross-checking of the mutually corroborated signals and thus delivers more reliable results for single-cell ROS analysis. Combined with the rich biomatter-light interplay, the concept of AEE can be extended to other stimuli-responsive aggregations for electrochemical innovations.

Altered dynamic amplitude of low-frequency fluctuation in individuals at high risk for Alzheimer's disease.

The brain's dynamic spontaneous neural activity is significant in supporting cognition; however, how brain dynamics go awry in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remains unclear. Thus, the current study aimed to investigate the dynamic amplitude of low-frequency fluctuation (dALFF) alterations in patients at high risk for Alzheimer's disease and to explore its correlation with clinical cognitive assessment scales, to identify an early imaging sign for these special populations. A total of 152 participants, including 72 SCD patients, 44 MCI patients and 36 healthy controls (HCs), underwent a resting-state functional magnetic resonance imaging and were assessed with various neuropsychological tests. The dALFF was measured using sliding-window analysis. We employed canonical correlation analysis (CCA) to examine the bi-multivariate correlations between neuropsychological scales and altered dALFF among multiple regions in SCD and MCI patients. Compared to those in the HC group, both the MCI and SCD groups showed higher dALFF values in the right opercular inferior frontal gyrus (voxel P < .001, cluster P < .05, correction). Moreover, the CCA models revealed that behavioural tests relevant to inattention correlated with the dALFF of the right middle frontal gyrus and right opercular inferior frontal gyrus, which are involved in frontoparietal networks (R = .43, P = .024). In conclusion, the brain dynamics of neural activity in frontal areas provide insights into the shared neural basis underlying SCD and MCI.

Logic Signal Amplification System for Sensitive Electrochemiluminescence Detection and Subtype Identification of Cancer Cells.

Achieving sensitive detection and accurate identification of cancer cells is vital for diagnosing and treating the disease. Here, we developed a logic signal amplification system using DNA tetrahedron-mediated three-dimensional (3D) DNA nanonetworks for sensitive electrochemiluminescence (ECL) detection and subtype identification of cancer cells. Specially designed hairpins were integrated into DNA tetrahedral nanostructures (DTNs) to perform a catalytic hairpin assembly (CHA) reaction in the presence of target microRNA, forming hyperbranched 3D nanonetworks. Benefiting from the "spatial confinement effect," the DNA tetrahedron-mediated catalytic hairpin assembly (DTCHA) reaction displayed significantly faster kinetics and greater cycle conversion efficiency than traditional CHA. The resulting 3D nanonetworks could load a large amount of Ru(phen)32+, significantly enhancing its ECL signal, and exhibit detection limits for both miR-21 and miR-141 at the femtomolar level. The biosensor based on modular logic gates facilitated the distinction and quantification of cancer cells and normal cells based on miR-21 levels, combined with miR-141 levels, to further identify different subtypes of breast cancer cells. Overall, this study provides potential applications in miRNA-related clinical diagnostics.

Endogenous AND Logic DNA Nanomachine for Highly Specific Cancer Cell Imaging.

Intracellular cancer-related biomarker imaging strategy has been used for specific identification of cancer cells, which was of great importance to accurate cancer clinical diagnosis and prognosis studies. Localized DNA circuits with improved sensitivity showed great potential for intracellular biomarkers imaging. However, the ability of localized DNA circuits to specifically image cancer cells is limited by off-site signal leakage associated with a single-biomarker sensing strategy. Herein, we integrated the endogenous enzyme-powered strategy with logic-responsive and localized signal amplifying capability to construct a self-assembled endogenously AND logic DNA nanomachine (EDN) for highly specific cancer cell imaging. When the EDN encountered a cancer cell, the overexpressed DNA repairing enzyme apurinic/apyrimidinic endonuclease 1 (APE1) and miR-21 could synergistically activate a DNA circuit via cascaded localized toehold-mediated strand displacement (TMSD) reactions, resulting in amplified fluorescence resonance energy transfer (FRET) signal. In this strategy, both endogenous APE1 and miR-21, served as two "keys" to activate the AND logic operation in cancer cells to reduce off-tumor signal leakage. Such a multiplied molecular recognition/activation nanomachine as a powerful toolbox realized specific capture and reliable imaging of biomolecules in living cancer cells.

Enhanced Aggregation-Induced Delayed Electrochemiluminescence Triggered by Spatial Perturbation of Organic Dots.

Development of highly efficient, heavy-metal-free electrochemiluminescence (ECL) materials is attractive but still challenging. Herein, we report an aggregation-induced delayed ECL (AIDECL) active organic dot (OD) composed of a tert-butoxy-group-substituted benzophenone-dimethylacridine compound, which shows high ECL efficiency. The resultant ODs exhibit 2.1-fold higher ECL efficiency compared to control AIDECL-active ODs. Molecular stacking combined with theoretical calculations suggests that tert-butoxy groups effectively participate in the intermolecular interactions, further inhibiting the molecular motions in the aggregated states and thus accelerating radiative decay. On the basis of these ODs exhibiting excellent ECL performance, a proof-of-concept biosensor is constructed for the detection of miR-16 associated with Alzheimer's disease, which demonstrates excellent detection ability with the limit of detection of 1.7 fM. This work provides a new approach to improve the ECL efficiency and enriches the fundamental understanding of the structure-property relationship.

High-Precision Single-Cell microRNA Therapy by a Functional Nanopipette with Sensitive Photoelectrochemical Feedback.

This work proposes the concept of single-cell microRNA (miR) therapy and proof-of-concept by engineering a nanopipette for high-precision miR-21-targeted therapy in a single HeLa cell with sensitive photoelectrochemical (PEC) feedback. Targeting the representative oncogenic miR-21, the as-functionalized nanopipette permits direct intracellular drug administration with precisely controllable dosages, and the corresponding therapeutic effects can be sensitively transduced by a PEC sensing interface that selectively responds to the indicator level of cytosolic caspase-3. The experimental results reveal that injection of ca. 4.4 × 10-20 mol miR-21 inhibitor, i.e., 26488 copies, can cause the obvious therapeutic action in the targeted cell. This work features a solution to obtain the accurate knowledge of how a certain miR-drug with specific dosages treats the cells and thus provides an insight into futuristic high-precision clinical miR therapy using personalized medicine, provided that the prerequisite single-cell experiments are courses of personalized customization.

Interfacial Hydrogen-Bond Interactions Driven Assembly toward Polychromatic Copper Nanoclusters.

Constructing versatile metal nanoclusters (NCs) assemblies through noncovalent weak interactions between inter-ligands is a long-standing challenge in interfacial chemistry, while compelling interfacial hydrogen-bond-driven metal NCs assemblies remain unexplored so far. Here, the study reports an amination-ligand o-phenylenediamine-coordinated copper NCs (CuNCs), demonstrating the impact of interfacial hydrogen-bonds (IHBs) motifs on the luminescent behaviors of metal NCs as the alteration of protic solvent. Experimental results supported by theoretical calculation unveil that the flexibility of interfacial ligand and the distance of cuprophilic CuI···CuI interaction between intra-/inter-NCs can be tailored by manipulating the cooperation between the diverse IHBs motifs reconstruction, therewith the IHBs-modulated fundamental structure-property relationships are established. Importantly, by utilizing the IHBs-mediated optical polychromatism of aminated CuNCs, portable visualization of humidity sensing test-strips with fast response is successfully manufactured. This work not only provides further insights into exploring the interfacial chemistry of NCs based on inter-ligands hydrogen-bond interactions, but also offers a new opportunity to expand the practical application for optical sensing of metal NCs.

Scalable Dual In Situ Synthesis of Polyester Nanocomposites for High-Energy Storage.

Incorporating ultralow loading of nanoparticles into polymers has realized increases in dielectric constant and breakdown strength for excellent energy storage. However, there are still a series of tough issues to be dealt with, such as organic solvent uses, which face enormous challenges in scalable preparation. Here, a new strategy of dual in situ synthesis is proposed, namely polymerization of polyethylene terephthalate (PET) synchronizes with growth of calcium borate nanoparticles, making polyester nanocomposites from monomers directly. Importantly, this route is free of organic solvents and surface modification of nanoparticles, which is readily accessible to scalable synthesis of polyester nanocomposites. Meanwhile, uniform dispersion of as ultralow as 0.1 wt% nanoparticles and intense bonding at interfaces have been observed. Furthermore, the PET-based nanocomposite displays obvious increases in both dielectric constant and breakdown strength as compared to the neat PET. Its maximum discharged energy density reaches 15 J cm-3 at 690 MV m-1 and power density attains 218 MW cm-3 under 150 Ω resistance at 300 MV m-1, which is far superior to the current dielectric polymers that can be produced at large scales. This work presents a scalable, safe, low-cost, and environment-friendly route toward polymer nanocomposites with superior capacitive performance.

Survey of hepatitis B virus infection status after 35 years of universal vaccination implementation in Taiwan.

BACKGROUND AND AIMS: Hepatitis B virus (HBV) vaccination programs in Taiwan are one of the earliest programs in the world and have largely reduced the prevalence of HBV infection. We aimed to demonstrate the vaccination efficacy after 35 years and identify gaps toward HBV elimination. METHODS: A total of 4717 individuals aged 1-60 years were recruited from four administrative regions based on the proportion of population distribution. Serum levels of hepatitis B surface antigen (HBsAg), hepatitis B surface antibody (anti-HBs), and hepatitis B core antibody (anti-HBc) levels were assessed. HBV viral load, genotypes and HBsAg 'ɑ' determinant variants were evaluated if indicated. RESULTS: After 35 years of vaccination, the overall seropositivity rates for HBsAg and anti-HBc in Taiwan were 4.05% and 21.3%, respectively. The vaccinated birth cohorts exhibited significantly lower seropositivity rates for both markers compared to the unvaccinated birth cohorts (HBsAg: 0.64% vs. 9.78%; anti-HBc: 2.1% vs. 53.55%, respectively; p < 0.0001). Maternal transmission was identified as the main route of HBV infection in breakthrough cases. Additionally, increased prevalences of genotype C and HBsAg escape mutants were observed. CONCLUSION: The 35-year universal HBV vaccination program effectively reduced the burden of HBV infection, but complete eradication of HBV infection has not yet been achieved. In addition to immunization, comprehensive screening and antiviral therapy for infected individuals, especially for pregnant women, are crucial strategies to eliminate HBV.

Tenofovir alafenamide or tenofovir disoproxil fumarate in pregnancy to prevent HBV transmission: Maternal ALT trajectory and infant outcomes.

BACKGROUND: The use of antiviral agents, specifically tenofovir disoproxil fumarate (TDF), in pregnant women to prevent mother-to-child HBV transmission is a key step towards hepatitis elimination. However, data on using tenofovir alafenamide (TAF) is insufficient. The frequent occurrence of postpartum ALT flares may impact the clinical implementation. METHODS: The maternal and infant outcomes were compared in multi-centre trials of high viral load HBsAg/HBeAg+ pregnant women receiving TAF or TDF from the third trimester until 2 weeks postpartum with intensive follow-ups. To explore the dynamic pre- and postpartum changes in ALT levels, we used a group-based trajectory model for analysing data of 332 women from three prospective studies. RESULTS: After treatment, the maternal HBV DNA levels significantly decreased from baseline to delivery: 7.87 ± 0.59 to 3.99 ± 1.07 Log10 IU/mL TAF (n = 78) and 8.30 ± 0.36 to 4.47 ± 0.86 Log10 IU/mL (TDF, n = 53), with viral load reductions of 3.87 versus 3.83 Log10 IU/mL. The HBsAg-positive rates among 12-month-old infants were 1.28% (1/78) versus 1.82% (1/55) respectively (p = 1.00). Of the TAF or TDF-treated mothers, 25.64% versus 16.98% experienced ALT > 2X ULN, and 11.54% versus 1.89% received extended antiviral treatment. Our model revealed four distinct ALT patterns: stable ALT (87.2%), moderate (8.0%) or marked (2.4%) postpartum flares, or prepartum elevations (2.4%). CONCLUSIONS: TAF effectively reduces mother-to-child HBV transmission, but prophylaxis failure still occurred in few cases. Postpartum ALT flares are common in women receiving TAF or TDF during pregnancy. Approximately 12.8% of mothers may require extended postpartum antiviral treatment. CLINICAL TRIAL NUMBER: NCT03695029 (ClinicalTrials.gov).

Deep-learning-based radiomics of intratumoral and peritumoral MRI images to predict the pathological features of adjuvant radiotherapy in early-stage cervical squamous cell carcinoma.

BACKGROUND: Surgery combined with radiotherapy substantially escalates the likelihood of encountering complications in early-stage cervical squamous cell carcinoma(ESCSCC). We aimed to investigate the feasibility of Deep-learning-based radiomics of intratumoral and peritumoral MRI images to predict the pathological features of adjuvant radiotherapy in ESCSCC and minimize the occurrence of adverse events associated with the treatment. METHODS: A dataset comprising MR images was obtained from 289 patients who underwent radical hysterectomy and pelvic lymph node dissection between January 2019 and April 2022. The dataset was randomly divided into two cohorts in a 4:1 ratio.The postoperative radiotherapy options were evaluated according to the Peter/Sedlis standard. We extracted clinical features, as well as intratumoral and peritumoral radiomic features, using the least absolute shrinkage and selection operator (LASSO) regression. We constructed the Clinical Signature (Clinic_Sig), Radiomics Signature (Rad_Sig) and the Deep Transformer Learning Signature (DTL_Sig). Additionally, we fused the Rad_Sig with the DTL_Sig to create the Deep Learning Radiomic Signature (DLR_Sig). We evaluated the prediction performance of the models using the Area Under the Curve (AUC), calibration curve, and Decision Curve Analysis (DCA). RESULTS: The DLR_Sig showed a high level of accuracy and predictive capability, as demonstrated by the area under the curve (AUC) of 0.98(95% CI: 0.97-0.99) for the training cohort and 0.79(95% CI: 0.67-0.90) for the test cohort. In addition, the Hosmer-Lemeshow test, which provided p-values of 0.87 for the training cohort and 0.15 for the test cohort, respectively, indicated a good fit. DeLong test showed that the predictive effectiveness of DLR_Sig was significantly better than that of the Clinic_Sig(P < 0.05 both the training and test cohorts). The calibration plot of DLR_Sig indicated excellent consistency between the actual and predicted probabilities, while the DCA curve demonstrating greater clinical utility for predicting the pathological features for adjuvant radiotherapy. CONCLUSION: DLR_Sig based on intratumoral and peritumoral MRI images has the potential to preoperatively predict the pathological features of adjuvant radiotherapy in early-stage cervical squamous cell carcinoma (ESCSCC).

Dynamic radiomics based on contrast-enhanced MRI for predicting microvascular invasion in hepatocellular carcinoma.

OBJECTIVE: To exploit the improved prediction performance based on dynamic contrast-enhanced (DCE) MRI by using dynamic radiomics for microvascular invasion (MVI) in hepatocellular carcinoma (HCC). METHODS: We retrospectively included 175 and 75 HCC patients who underwent preoperative DCE-MRI from September 2019 to August 2022 in institution 1 (development cohort) and institution 2 (validation cohort), respectively. Static radiomics features were extracted from the mask, arterial, portal venous, and equilibrium phase images and used to construct dynamic features. The static, dynamic, and dynamic-static radiomics (SR, DR, and DSR) signatures were separately constructed based on the feature selection method of LASSO and classification algorithm of logistic regression. The receiver operating characteristic (ROC) curves and the area under the curve (AUC) were plotted to evaluate and compare the predictive performance of each signature. RESULTS: In the three radiomics signatures, the DSR signature performed the best. The AUCs of the SR, DR, and DSR signatures in the training set were 0.750, 0.751 and 0.805, respectively, while in the external validation set, the corresponding AUCs were 0.706, 0756 and 0.777. The DSR signature showed significant improvement over the SR signature in predicting MVI status (training cohort: P = 0.019; validation cohort: P = 0.044). After external validation, the AUC value of the SR signature decreased from 0.750 to 0.706, while the AUC value of the DR signature did not show a decline (AUCs: 0.756 vs. 0.751). CONCLUSIONS: The dynamic radiomics had an improved effect on the MVI prediction in HCC, compared with the static DCE MRI-based radiomics models.

Single-molecule calorimeter and free energy landscape.

The precise measurement of thermodynamic and kinetic properties for biomolecules provides the detailed information for a multitude of applications in biochemistry, biosensing, and health care. However, sensitivity in characterizing the thermodynamic binding affinity down to a single molecule, such as the Gibbs free energy ([Formula: see text]), enthalpy ([Formula: see text]), and entropy ([Formula: see text]), has not materialized. Here, we develop a nanoparticle-based technique to probe the energetic contributions of single-molecule binding events, which introduces a focused laser of optical tweezer to an optical path of plasmonic imaging to accumulate and monitor the transient local heating. This single-molecule calorimeter uncovers the complex nature of molecular interactions and binding characterizations, which can be employed to identify the thermodynamic equilibrium state and determine the energetic components and complete thermodynamic profile of the free energy landscape. This sensing platform promises a breakthrough in measuring thermal effect at the single-molecule level and provides a thorough description of biomolecular specific interactions.