Protein folding dependence on selenoprotein M contributes to steady cartilage extracellular matrix repressing ferroptosis via PERK/ATF4/CHAC1 axis.

OBJECTIVE: Initiation of endoplasmic reticulum (ER) stress is pivotal to the advancement of osteoarthritis (OA). We aimed to explore the function of ER-resident selenoprotein M (SELM) in cartilage-forming chondrocytes, investigating how SELM participates in cartilage extracellular matrix (ECM) metabolism and ER stress modulation. METHODS: Articular cartilage samples with knee OA undergoing total knee arthroplasty were categorised into OA-smooth and OA-damaged groups, with primary chondrocytes extracted from smooth areas. Destabilization of the medial meniscus was induced in male C57BL6/J mice, with sham operations on the left knee as controls. After 8 weeks, knee joint tissues were collected for analysis. Histology and immunohistochemistry examined cartilage damage. Molecular biology techniques investigated how SELM affects ECM metabolism and ER stress regulation. RNA sequencing revealed the pathway changes after SELM intervention. AlphaFold demonstrated how SELM interacts with other molecules. Cultured cartilage explants helped determine the effects of SELM supplementation. RESULTS: SELM expression was reduced in the damaged cartilage. Increasing SELM levels positively impacted ECM equilibrium. Decreasing SELM expression activated genes linked to degenerative ailments and impaired the cellular response to misfolded proteins, initiating the PERK/P-EIF2A/ATF4 pathway and exacerbating GSH/GSSG imbalance via the ATF4/CHAC1 axis. SELM likely participated in protein folding and modification by leveraging its thioredoxin domains. In vitro SELM supplementation mitigated IL-1ß effects on damaged cartilage explants and suppressed beneficial chondrocyte phenotypes. CONCLUSIONS: Our results confirm the involvement of SELM in ER stress-induced cartilage damage as well as protein folding, pointing to new directions in molecular therapy for degenerative diseases.

Diosmetin Promotes Early Embryonic Development in Pigs by Alleviating Oxidative Stress.

Diosmetin (DIOS), a natural flavonoid monomer derived from lemons and present in various plants such as spearmint and spider moss, exhibits antioxidant, anti-inflammatory, and antiaging properties. Nonetheless, its impact on early embryonic development in pigs remains unexplored. This study aimed to determine the influence of DIOS supplementation in an in vitro culture (IVC) medium on porcine embryo development and to elucidate the underlying mechanisms. Findings revealed that embryos cultured in IVC medium with 0.1 µM DIOS demonstrated an increased blastocyst formation rate, higher total cell number, reduced LC3B and CASPASE3 levels, elevated Nrf2 levels, decreased ROS, and enhanced GSH and mitochondrial membrane potential at the 4-cell embryonic stage. Additionally, the expression of proapoptotic genes (CAS3, CAS8, and BAX) and autophagy-related genes (BECLIN1, ATG5, LC3B, and P62) was downregulated, whereas the expression of embryonic development-related genes (CDK1 and CDK2), antioxidant-related genes (SOD1 and SOD2), and mitochondrial biogenesis-related genes (NRF2) was upregulated. These findings suggest that DIOS promotes early embryonic development in pigs by mitigating oxidative stress and enhancing mitochondrial function, thereby reducing autophagy and apoptosis levels.

Improved memory truncation scheme for quasi-adiabatic propagator path integral via influence functional renormalization.

Accurately simulating non-Markovian quantum dynamics in system-bath coupled problems remains challenging. In this work, we present a novel memory truncation scheme for the iterative quasi-adiabatic propagator path integral (iQuAPI) method to improve accuracy. Conventional memory truncation in iQuAPI discards all influence functional beyond a certain time interval, which is not effective for problems with a long memory time. Our proposed scheme selectively retains the most significant parts of the influence functional using the density matrix renormalization group algorithm. We validate the effectiveness of our scheme through simulations of the spin-boson model across various parameter sets, demonstrating faster convergence and improved accuracy compared to the conventional scheme. Our findings suggest that the new memory truncation scheme significantly advances the capabilities of iQuAPI for problems with a long memory time.

Optimal tree tensor network operators for tensor network simulations: Applications to open quantum systems.

Tree tensor network states (TTNS) decompose the system wavefunction to the product of low-rank tensors based on the tree topology, serving as the foundation of the multi-layer multi-configuration time-dependent Hartree method. In this work, we present an algorithm that automatically constructs the optimal and exact tree tensor network operators (TTNO) for any sum-of-product symbolic quantum operator. The construction is based on the minimum vertex cover of a bipartite graph. With the optimal TTNO, we simulate open quantum systems, such as spin relaxation dynamics in the spin-boson model and charge transport in molecular junctions. In these simulations, the environment is treated as discrete modes and its wavefunction is evolved on equal footing with the system. We employ the Cole-Davidson spectral density to model the glassy phonon environment and incorporate temperature effects via thermo-field dynamics. Our results show that the computational cost scales linearly with the number of discretized modes, demonstrating the efficiency of our approach.

Intermolecular Charge-Transfer-Induced Strong Optical Emission from Herringbone H-Aggregates.

Luminescence in molecular aggregates can be quenched either by intermolecular charge transfer or by forming a dipole-forbidden lower Frenkel exciton in H-aggregate. Taking intermolecular charge transfer and excitonic coupling into a three-state model through localized diabatization, we demonstrate that the low-lying intermolecular charge-transfer state could couple with the upper bright Frenkel exciton to form dipole-allowed S1 that lies below the dark state, which accounts for the recent experimentally discovered strong luminescence in organic light-emitting transistors (OLETs) system with DPA and dNaAnt herringbone aggregates. The condition of forming such bright state is that the electron and hole transfer integrals, te and th, are of the same sign, and should be notably larger than the excitonic coupling (J), that is , te × th > 2J2. This theoretical finding not only rationalizes recent experiments but unravels an exciting scenario where strong luminescence and high charge mobilities become compatible, which is a preferable condition for both OLETs and electrically pumped lasing.

Induction of PDCD4 by albumin in proximal tubule epithelial cells potentiates proteinuria-induced dysfunctional autophagy by negatively targeting Atg5.

Autophagy dysfunction is a hallmark of type 1 diabetes. However, the precise molecular mechanism of proteinuria-induced dysfunctional autophagy remains unclear. Herein, we investigated the role of programmed cell death 4 (PDCD4) in the regulation of autophagy in the pathogenesis of diabetic kidney disease (DKD) in vivo and in vitro. RT-qPCR, immunohistochemistry (IHC), and western blotting demonstrated an upregulation of Pdcd4 mRNA and protein in streptozotocin (STZ)-induced DKD rats, as compared to the control. In addition, IHC and western blotting of a unilateral ureteral obstruction mouse model showed an upregulation of PDCD4 in the disease group, as compared to their respective controls. IHC analysis of kidney biopsy samples of human DKD patients showed an upregulation of PDCD4 compared to the control. Western blotting of the STZ-induced DKD rat tissues displayed a low microtubule-associated protein 1A/1B-light chain 3 (LC3)-II, as compared to the control. It was found that albumin overload in cultured PTECs upregulated the expression of PDCD4 and p62 and decreased the expression of LC3-II and autophagy-related 5 (Atg5) proteins. The knockout of Pdcd4 in cultured PTECs could reduce albumin-induced dysfunctional autophagy, as evidenced by the recovery of Atg5 and LC3-II protein. The forced expression of PDCD4 could further suppress the expression of the crucial autophagy-related gene Atg5. Evidence suggests that endogenous PDCD4 promotes proteinuria-induced dysfunctional autophagy by negatively regulating Atg5. Therefore, PDCD4 may be a potential therapeutic target in DKD.

Imaging error compensation method for through-focus scanning optical microscopy images based on deep learning.

Through-focus scanning optical microscopy (TSOM) is a model-based nanoscale metrology technique which combines conventional bright-field microscopy and the relevant numerical simulations. A TSOM image is generated after through-focus scanning and data processing. However, the mechanical vibration and optical noise introduced into the TSOM image during image generation can affect the measurement accuracy. To reduce this effect, this paper proposes a imaging error compensation method for the TSOM image based on deep learning with U-Net. Here, the simulated TSOM image is regarded as the ground truth, and the U-Net is trained using the experimental TSOM images by means of a supervised learning strategy. The experimental TSOM image is first encoded and then decoded with the U-shaped structure of the U-Net. The difference between the experimental and simulated TSOM images is minimised by iteratively updating the weights and bias factors of the network, to obtain the compensated TSOM image. The proposed method is applied for optimising the TSOM images for nanoscale linewidth estimation. The results demonstrate that the proposed method performs as expected and provides a significant enhancement in accuracy.

A through-focus scanning optical microscopy dimensional measurement method based on deep-learning classification model.

Through-focus scanning optical microscopy (TSOM) is an economical, non-contact and nondestructive method for rapid measurement of three-dimensional nanostructures. There are two methods using TSOM image to measure the dimensions of one sample, including the library-matching method and the machine-learning regression method. The first has the defects of small measurement range and strict environmental requirements; the other has the disadvantages of feature extraction method greatly influenced by human subjectivity and low measurement accuracy. To solve the problems above, a TSOM dimensional measurement method based on deep-learning classification model is proposed. TSOM images are used to train the ResNet50 and DenseNet121 classification model respectively in this paper, and the test images are used to test the model, the classification result of which is taken as the measurement value. The test results showed that with the number of training linewidths increasing, the mean square error (MSE) of the test images is 21.05 nm² for DenseNet121 model and 31.84 nm² for ResNet50 model, both far lower than machine-learning regression method, and the measurement accuracy is significantly improved. The feasibility of using deep-learning classification model, instead of machine-learning regression model, for dimensional measurement is verified, providing a theoretical basis for further improvement on the accuracy of dimensional measurement.

Evaluating the anharmonicity contributions to the molecular excited state internal conversion rates with finite temperature TD-DMRG.

In this work, we propose a new method to calculate molecular nonradiative electronic relaxation rates based on the numerically exact time-dependent density matrix renormalization group theory. This method could go beyond the existing frameworks under the harmonic approximation (HA) of the potential energy surface (PES) so that the anharmonic effect could be considered, which is of vital importance when the electronic energy gap is much larger than the vibrational frequency. We calculate the internal conversion (IC) rates in a two-mode model with Morse potential to investigate the validity of HA. We find that HA is unsatisfactory unless only the lowest several vibrational states of the lower electronic state are involved in the transition process when the adiabatic excitation energy is relatively low. As the excitation energy increases, HA first underestimates and then overestimates the IC rates when the excited state PES shifts toward the dissociative side of the ground state PES. On the contrary, HA slightly overestimates the IC rates when the excited state PES shifts toward the repulsive side. In both cases, a higher temperature enlarges the error of HA. As a real example to demonstrate the effectiveness and scalability of the method, we calculate the IC rates of azulene from S1 to S0 on the ab initio anharmonic PES approximated by the one-mode representation. The calculated IC rates of azulene under HA are consistent with the analytically exact results. The rates on the anharmonic PES are 30%-40% higher than the rates under HA.

Simultaneously and Selectively Imaging a Cytoplasm Membrane and Mitochondria Using a Dual-Colored Aggregation-Induced Emission Probe.

Analysis of subcellular organelles (e.g., a cytoplasm membrane and mitochondria) during cellular processes can provide particularly useful information for our understanding of cell chemistry and biology. For this purpose, fluorescent probes capable of dynamically imaging multiple organelles in a simultaneous and selective manner are highly demanded, yet such probes are scarcely reported due to the challenges in molecular design. In this study, we developed a dual-colored aggregation-induced emission (AIE) probe TPNPDA-C12 with twisted intramolecular charge transfer (TICT) to visualize the membrane and mitochondria of the same cells through distinct fluorescence channels simultaneously. We also successfully used the probe to monitor and distinguish the dynamic changes of the organelles during cell apoptosis and necrosis induced by reactive oxygen species (ROS) and cytotoxins.

Numerical assessment for accuracy and GPU acceleration of TD-DMRG time evolution schemes.

The time dependent density matrix renormalization group (TD-DMRG) has become one of the cutting edge methods of quantum dynamics for complex systems. In this paper, we comparatively study the accuracy of three time evolution schemes in the TD-DMRG, the global propagation and compression method with the Runge-Kutta algorithm (P&C-RK), the time dependent variational principle based methods with the matrix unfolding algorithm (TDVP-MU), and with the projector-splitting algorithm (TDVP-PS), by performing benchmarks on the exciton dynamics of the Fenna-Matthews-Olson complex. We show that TDVP-MU and TDVP-PS yield the same result when the time step size is converged and they are more accurate than P&C-RK4, while TDVP-PS tolerates a larger time step size than TDVP-MU. We further adopt the graphical processing units to accelerate the heavy tensor contractions in the TD-DMRG, and it is able to speed up the TDVP-MU and TDVP-PS schemes by up to 73 times.

A general automatic method for optimal construction of matrix product operators using bipartite graph theory.

Constructing matrix product operators (MPOs) is at the core of the modern density matrix renormalization group (DMRG) and its time dependent formulation. For the DMRG to be conveniently used in different problems described by different Hamiltonians, in this work, we propose a new generic algorithm to construct the MPO of an arbitrary operator with a sum-of-products form based on the bipartite graph theory. We show that the method has the following advantages: (i) it is automatic in that only the definition of the operator is required; (ii) it is symbolic thus free of any numerical error; (iii) the complementary operator technique can be fully employed so that the resulting MPO is globally optimal for any given order of degrees of freedom; and (iv) the symmetry of the system could be fully employed to reduce the dimension of MPO. To demonstrate the effectiveness of the new algorithm, the MPOs of Hamiltonians ranging from the prototypical spin-boson model and the Holstein model to the more complicated ab initio electronic Hamiltonian and the anharmonic vibrational Hamiltonian with the sextic force field are constructed. It is found that for the former three cases, our automatic algorithm can reproduce exactly the same MPOs as the optimally hand-crafted ones already known in the literature.

Applying Marcus theory to describe the carrier transports in organic semiconductors: Limitations and beyond.

Marcus theory has been successfully applied to molecular design for organic semiconductors with the aid of quantum chemistry calculations for the molecular parameters: the intermolecular electronic coupling V and the intramolecular charge reorganization energy λ. The assumption behind this is the localized nature of the electronic state for representing the charge carriers, being holes or electrons. As far as the quantitative description of carrier mobility is concerned, the direct application of Marcus semiclassical theory usually led to underestimation of the experimental data. A number of effects going beyond such a semiclassical description will be introduced here, including the quantum nuclear effect, dynamic disorder, and delocalization effects. The recently developed quantum dynamics simulation at the time-dependent density matrix renormalization group theory is briefly discussed. The latter was shown to be a quickly emerging efficient quantum dynamics method for the complex system.

Comparison of drug-eluting balloon versus drug-eluting stent for treatment of coronary artery disease: a meta-analysis of randomized controlled trials.

BACKGROUND: Drug-eluting balloons (DEB) have significant value for treating coronary artery disease (CAD). However, the merits of using DEB versus drug-eluting stents (DES) to treat CAD remain controversial. Herein, we conducted a meta-analysis to compare the safety and efficacy of DEB and DES for treatment of CAD. METHODS: We searched MEDLINE, EMBASE, and CENTRAL databases for eligible trials comparing DEB with DES for treatment of CAD. The primary endpoint was major adverse cardiac events (MACE); the secondary endpoints included in-lesion late lumen loss (LLL), binary restenosis (BR), myocardial infarction (MI), target lesion revascularization (TLR) and mortality. RESULTS: Twenty-three trials with a total of 2712 patients were included. There were no significant differences in the primary endpoint of MACE between the DEB and DES groups (Risk Ratio (RR) 1.19; 95% confidence interval (CI) (0.87, 1.63); P = 0.27), or in the clinical outcomes of each of MACE's components, including TLR, MI and mortality. However, efficacy was significantly different between the DEB and DES groups, especially when we compared DEB to second-generation DES: in-lesion LLL (Mean Difference (MD) 0.11; (0.01, 0.22); P = 0.03); binary restenosis (RR 1.46; (1.00, 2.13); P = 0.05). CONCLUSIONS: DEB is equivalent to DES in terms of safety for managing CAD, and DEB may be considered as an alternative choice for treatment of CAD.

FTO ameliorates doxorubicin-induced cardiotoxicity by inhibiting ferroptosis via P53-P21/Nrf2 activation in a HuR-dependent m6A manner.

Doxorubicin (DOX)-induced cardiotoxicity seriously limits its clinical applicability, and no therapeutic interventions are available. Ferroptosis, an iron-dependent regulated cell death characterised by lipid peroxidation, plays a pivotal role in DOX-induced cardiotoxicity. N6-methyladenosine (m6A) methylation is the most frequent type of RNA modification and involved in DOX-induced ferroptosis, however, its underlying mechanism remains unclear. P21 was recently found to inhibit ferroptosis by interacting with Nrf2 and is regulated in a P53-dependent or independent manner, such as through m6A modification. In the present study, we investigated the mechanism underlying m6A modification in DOX-induced ferroptosis by focusing on P21. Our results show that fat mass and obesity-associated protein (FTO) down-regulation was associated with DOX-induced cardiotoxicity. FTO over-expression significantly improved cardiac function and cell viability in DOX-treated mouse hearts and H9C2 cells. FTO over-expression significantly inhibited DOX-induced ferroptosis, and the Fer-1 inhibition of ferroptosis significantly reduced DOX-induced cardiotoxicity. P21 was significantly upregulated by FTO and activated Nrf2, playing a crucial role in the anti-ferroptotic effect. FTO upregulated P21/Nrf2 in a P53-dependent manner by mediating the demethylation of P53 or in a P53-independent manner by mediating P21/Nrf2 directly. Human antigen R (HuR) is crucial for FTO-mediated regulation of ferroptosis and P53-P21/Nrf2. Notably, we also found that P21 inhibition in turn inhibited HuR and P53 expression, while HuR inhibition further inhibited FTO expression. RNA immunoprecipitation assay showed that HuR binds to the transcripts of FTO and itself. Collectively, FTO inhibited DOX-induced ferroptosis via P21/Nrf2 activation by mediating the m6A demethylation of P53 or P21/Nrf2 in a HuR-dependent manner and constituted a positive feedback loop with HuR and P53-P21. Our findings provide novel insight into key functional mechanisms associated with DOX-induced cardiotoxicity and elucidate a possible therapeutic approach.

Physics-Constrained Hardware-Efficient Ansatz on Quantum Computers That Is Universal, Systematically Improvable, and Size-Consistent.

Variational wave function ansätze are at the heart of solving quantum many-body problems in physics and chemistry. Previous designs of hardware-efficient ansatz (HEA) on quantum computers are largely based on heuristics and lack rigorous theoretical foundations. In this work, we introduce a physics-constrained approach for designing HEA with rigorous theoretical guarantees by imposing a few fundamental constraints. Specifically, we require that the target HEA to be universal, systematically improvable, and size-consistent, which is an important concept in quantum many-body theories for scalability but has been overlooked in previous designs of HEA. We extend the notion of size-consistency to HEA and present a concrete realization of HEA that satisfies all these fundamental constraints while only requiring linear qubit connectivity. The developed physics-constrained HEA is superior to other heuristically designed HEA in terms of both accuracy and scalability, as demonstrated numerically for the Heisenberg model and some typical molecules. In particular, we find that restoring size-consistency can significantly reduce the number of layers needed to reach a certain accuracy. In contrast, the failure of other HEA to satisfy these constraints severely limits their scalability to larger systems with more than 10 qubits. Our work highlights the importance of incorporating physical constraints into the design of HEA for efficiently solving many-body problems on quantum computers.

Isoorientin Promotes Early Porcine Embryonic Development by Alleviating Oxidative Stress and Improving Lipid Metabolism.

Isoorientin (ISO) is a natural lignan glycoside flavonoid found in various plants, including Charcot and Stonecrop. ISO exhibits diverse physiological and pharmacological effects, such as antioxidative, anti-inflammatory, hepatoprotective, antiviral, antianxiety, and anti-myocardial ischaemic properties, as well as lipid metabolism regulation. This study investigated the impact of ISO supplementation on oxidative stress and lipid accumulation in porcine early embryos, along with its underlying mechanisms. Porcine embryos were cultured in vitro under different concentrations of ISO (0, 1, 10, and 100 nM). The results revealed that 10 nM ISO significantly enhanced the blastocyst rate and total embryonic cell count in vitro. ISO-treated embryos exhibited reduced reactive oxygen species levels and elevated glutathione levels compared to the untreated group. In addition, ISO treatment significantly increased the expression of the key antioxidant regulator Nrf2, improved mitochondrial function, and reduced lipid droplet accumulation. Concurrently, early embryo autophagy and apoptosis levels decreased. Furthermore, ISO treatment upregulated antioxidant-related genes (SOD1, SOD2, and CAT) and mitochondrial biogenesis related genes (NRF1, NRF2, and SIRT1), while downregulating lipid synthesis-related genes (SREBP1 and FASN). Additionally, lipid hydrolysis-related genes (ACADS) were elevated. These findings collectively suggest that ISO may facilitate early embryonic development in pigs by ameliorating oxidative stress and lipid metabolism.

History of tobacco smoking and alcohol use can predict the effectiveness of electroconvulsive therapy in individuals with schizophrenia: A multicenter clinical trial.

BACKGROUND: Current research has found that factors such as gender, age, and family history can predict the efficacy of electroconvulsive therapy (ECT) in individuals with schizophrenia. In our clinical practice, we anecdotally observed that tobacco smokers and alcohol drinkers with schizophrenia seemed to respond more effectively to ECT than non-smokers and non-drinkers. The current study aimed to examine whether history of tobacco smoking or alcohol consumption serve as indicators for predicting therapeutic efficacy of ECT in individuals with schizophrenia. METHODS: A total of 481 individuals receiving ECT combined with antipsychotic medication (ECT + AP medication) completed a two-week (six sessions of ECT) follow-up; 106 individuals receiving only antipsychotic medication (AP medication) also completed a two-week follow-up. Smoking, alcohol consumption, and AP medication usage was recorded for these individuals. Severity of psychotic symptoms was assessed using the Positive and Negative Syndrome Scale (PANSS). RESULTS: ECT + AP medication: Compared to schizophrenic individuals without a history of smoking (non-smokers), those with a history of smoking (smokers) showed a high decrease in negative symptoms (36.96% vs 24.76%; F = 5.974, p = 0.015). While, compared to individuals without a history of alcohol consumption (non-drinkers), those with a history of alcohol consumption (drinkers) showed a high decrease in positive symptoms (48.90% vs 41.47%; F = 5.074, p = 0.025). AP medication: No differences were found in symptom reduction between smokers and non-smokers or between drinkers and non-drinkers (p > 0.05). CONCLUSIONS: Smoking history in schizophrenic individuals independently predicts better improvement in negative symptoms after ECT, while alcohol consumption history independently predicts better improvement in positive symptoms after ECT. This is a clinically significant finding.

Surface Defect Detection for Automated Tape Laying and Winding Based on Improved YOLOv5.

To address the issues of low detection accuracy, slow detection speed, high missed detection rate, and high false detection rate in the detection of surface defects on pre-impregnated composite materials during the automated tape laying and winding process, an improved YOLOv5 (You Only Look Once version 5) algorithm model was proposed to achieve the high-precision, real-time detection of surface defects. By leveraging this improvement, the necessity for frequent manual interventions, inspection interventions, and subsequent rework during the automated lay-up process of composite materials can be significantly reduced. Firstly, to improve the detection accuracy, an attention mechanism called "CA (coordinate attention)" was introduced to enhance the feature extraction ability, and a Separate CA structure was used to improve the detection speed. Secondly, we used an improved loss function "SIoU (SCYLLA-Intersection over Union) loss" to replace the original "CIoU (Complete-Intersection over Union) loss", which introduced an angle loss as a penalty term to consider the directional factor and improve the stability of the target box regression. Finally, Soft-SIoU-NMS was used to replace the original NMS (non-maximum suppression) of YOLOv5 to improve the detection of overlapping defects. The results showed that the improved model had a good detection performance for surface defects on pre-impregnated composite materials during the automated tape laying and winding process. The FPS (frames per second) increased from 66.7 to 72.1, and the mAP (mean average precision) of the test set increased from 92.6% to 97.2%. These improvements ensured that the detection accuracy, as measured by the mAP, surpassed 95%, while maintaining a detection speed of over 70 FPS, thereby meeting the requirements for real-time online detection.

Unified Definition of Exciton Coherence Length for Exciton-Phonon Coupled Molecular Aggregates.

Exciton coherence length (ECL) characterizes the spatial extent of coherently delocalized excited states of molecular aggregates. Constructive/destructive superpositions of coherent molecular dipoles lead to superradiance/subradiance, where the radiative rate is enhanced/suppressed compared to that of a single molecule. Longer ECLs correspond to faster/slower radiative rates for superradiant/subradiant aggregates. However, previous ECL definitions fail to produce monotonic relationships when exciton-phonon coupling is considered, even for simple 1D exciton-phonon systems. This problem is exacerbated for 2D aggregates with both constructive and destructive superpositions. In this Letter, we propose a novel ECL definition by virtue of sum rule for oscillator strengths, ensuring a bijective and monotonic relationship between ECL and radiative rate for both 1D/2D superradiant and subradiant aggregates. Using numerically accurate time-dependent matrix product states, we study large-scale, exciton-phonon coupled 2D aggregates and predict the existence of maximum superradiance at finite temperature, in contrast to the previously believed 1/T law. Our results provide new insights into the design and optimization of efficient light emitting materials.