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This study examines whether the mandatory adoption of International Financial Reporting Standards (IFRS) in the European Union (EU) in 2005 reduces the cost of equity capital. Using a sample of 6,456 firm-year observations of 1,084 EU firms during the 1995 to 2006 period, I find evidence that, on average, the IFRS mandate significantly reduces the cost of equity for mandatory adopters by 47 basis points. I also find that this reduction is present only in countries with strong legal enforcement, and that increased disclosure and enhanced information comparability are two mechanisms behind the cost of equity reduction. Taken together, these findings suggest that while mandatory IFRS adoption significantly lowers firms' cost of equity, the effects depend on the strength of the countries' legal enforcement.

Deep analysis of next-generation sequencing data unveils numerous small non-coding RNAs with distinct functions. Recently, fragments derived from tRNA, named as tRNA-derived small RNA (tsRNA), have attracted broad attention. There are mainly two types of tsRNAs, including tRNA-derived stress-induced RNA (tiRNA) and tRNA-derived fragment (tRF), which differ in the cleavage position of the precursor or mature tRNA transcript. Emerging evidence has shown that tsRNAs are not merely tRNA degradation debris but have been recognized to play regulatory roles in many specific physiological and pathological processes. In this review, we summarize the biogeneses of various tsRNAs, present the emerging concepts regarding functions and mechanisms of action of tsRNAs, highlight the potential application of tsRNAs in human diseases, and put forward the current problems and future research directions.

While deep learning (DL) models exhibit superior simulation accuracy over traditional distributed hydrological models (DHMs), their main limitations lie in opacity and the absence of underlying physical mechanisms. The pursuit of synergies between DL and DHMs is an engaging research domain, yet a definitive roadmap remains elusive. In this study, a novel framework that seamlessly integrates a process‐based hydrological model encoded as a neural network (NN), an additional NN for mapping spatially distributed and physically meaningful parameters from watershed attributes, and NN‐based replacement models representing inadequately understood processes is developed. Multi‐source observations are used as training data, and the framework is fully differentiable, enabling fast parameter tuning by backpropagation. A hybrid DL model of the Amazon Basin (∼6 × 106 km2) was established based on the framework, and HydroPy, a global‐scale DHM, was encoded as its physical backbone. Trained simultaneously with streamflow observations and Gravity Recovery and Climate Experiment satellite data, the hybrid model yielded median Nash‐Sutcliffe efficiencies of 0.83 and 0.77 for dynamic and distributed simulations of streamflow and total water storage, respectively, 41% and 35% higher than those of the original HydroPy model. Replacing the original Penman‒Monteith formulation in HydroPy with a replacement NN produces more plausible potential evapotranspiration (PET) estimates, and unravels the spatial pattern of PET in this giant basin. The NN used for parameterization was interpreted to identify the factors controlling the spatial variability in key parameters. Overall, this study lays out a feasible technical roadmap for distributed hydrological modeling in the big data era. Key Points A fully differentiable framework that seamlessly integrates physics and deep learning was developed for distributed hydrological modeling The framework flexibly fuses multi‐source observations and improves the efficiency and accuracy of large‐scale hydrological modeling The hybrid model for the Amazon Basin exhibits excellent fidelity and physical plausibility and provides insights into the ET process

We test whether mandatory IFRS adoption affects firm-level \"crash risk,\" defined as the frequency of extreme negative stock returns. We separately analyze nonfinancial firms and financial firms because IFRS is likely to affect their crash risk differently. We find that IFRS adoption decreases crash risk among nonfinancial firms, especially among firms in poor information environments and in countries where IFRS adoption results in larger and more credible changes to local GAAP. In contrast, IFRS adoption has no effect on crash risk for financial firms, on average, but decreases crash risk among firms less affected by IFRS's fair value provisions, and increases crash risk among banks in countries with weak banking regulations. Overall, our results are consistent with the increased transparency from IFRS adoption broadly reducing crash risk among nonfinancial firms, but more selectively among financial firms, and with financial regulations playing a complementary role in implementing IFRS among financial firms.

Sepsis-associated encephalopathy (SAE) is one of the most common types of organ dysfunction without overt central nervous system (CNS) infection. It is associated with higher mortality, low quality of life, and long-term neurological sequelae, its mortality in patients diagnosed with sepsis, progressing to SAE, is 9% to 76%. The pathophysiology of SAE is still unknown, but its mechanisms are well elaborated, including oxidative stress, increased cytokines and proinflammatory factors levels, disturbances in the cerebral circulation, changes in blood–brain barrier permeability, injury to the brain’s vascular endothelium, altered levels of neurotransmitters, changes in amino acid levels, dysfunction of cerebral microvascular cells, mitochondria dysfunction, activation of microglia and astrocytes, and neuronal death. The diagnosis of SAE involves excluding direct CNS infection or other types of encephalopathies, which might hinder its early detection and appropriate implementation of management protocols, especially in paediatric patients where only a few cases have been reported in the literature. The most commonly applied diagnostic tools include electroencephalography, neurological imaging, and biomarker detection. SAE treatment mainly focuses on managing underlying conditions and using antibiotics and supportive therapy. In contrast, sedative medication is used judiciously to treat those showing features such as agitation. The most widely used medication is dexmedetomidine which is neuroprotective by inhibiting neuronal apoptosis and reducing a sepsis-associated inflammatory response, resulting in improved short-term mortality and shorter time on a ventilator. Other agents, such as dexamethasone, melatonin, and magnesium, are also being explored in vivo and ex vivo with encouraging results. Managing modifiable factors associated with SAE is crucial in improving generalised neurological outcomes. From those mentioned above, there are still only a few experimentation models of paediatric SAE and its treatment strategies. Extrapolation of adult SAE models is challenging because of the evolving brain and technical complexity of the model being investigated. Here, we reviewed the current understanding of paediatric SAE, its pathophysiological mechanisms, diagnostic methods, therapeutic interventions, and potential emerging neuroprotective agents.

Extraversion is the best and most consistent predictor of important leadership outcomes. However, there has been little exploration and examination of the mechanisms underlying the effects of extraverted leadership on performance. Drawing on distal-proximal motivational theory and situational strength theory, the present study proposes and examines a moderated mediation model that explains how leader extraversion affects team performance and how situational characteristics strengthen or constrain this relationship. Respondents were recruited through management team training courses run by the eight Chinese companies. We conducted two rounds of electronic questionnaire collection. The first round of data was collected during the training session. Four weeks later, we collected the data through the training courses’ WeChat groups. Data collected from 226 Chinese team leaders was analyzed using SPSS 26 and Mplus 7. We find that leader extraversion predicts team performance through a motivational mechanism operationalized as leader work engagement. We further find that goal clarity and process clarity play an important role in strengthening the positive effect of leader extraversion on leader work engagement as well as the motivational mechanism, providing an empirical explanation of how leader extraversion affects team performance through a motivational mechanism operationalized as leader work engagement. We also explore how two potential situational characteristics, operationalized as goal clarity and process clarity of leaders, affect the relationship between leader extraversion and leader work engagement as well as the motivational mechanism. Addionally, the findings suggest important practical implications for the organizations seeking to identify effective team leaders.

Circular RNAs (circRNAs) produced from back-spliced exons are widely expressed, but individual circRNA functions remain poorly understood owing to the lack of adequate methods for distinguishing circRNAs from cognate messenger RNAs with overlapping exons. Here, we report that CRISPR–RfxCas13d can effectively discriminate circRNAs from mRNAs by using guide RNAs targeting sequences spanning back-splicing junction (BSJ) sites featured in RNA circles. Using a lentiviral library that targets sequences across BSJ sites of highly expressed human circRNAs, we show that a group of circRNAs are important for cell growth mostly in a cell-type-specific manner and that a common oncogenic circRNA, circFAM120A, promotes cell proliferation by preventing the mRNA for family with sequence similarity 120A (FAM120A) from binding the translation inhibitor IGF2BP2. Further application of RfxCas13d–BSJ-gRNA screening has uncovered circMan1a2, which has regulatory potential in mouse embryo preimplantation development. Together, these results establish CRISPR–RfxCas13d as a useful tool for the discovery and functional study of circRNAs at both individual and large-scale levels.This paper describes a CRISPR–Cas13 system to effectively target circRNAs and screen their functions in vitro and in vivo, which enables the study of relevant circRNA phenotypes in human cell proliferation and in mouse embryogenesis.

Atezolizumab (anti-PD-L1) combined with bevacizumab (anti-VEGFA) is the first-line immunotherapy for advanced hepatocellular carcinoma (HCC), but the number of patients who benefit from this regimen remains limited. Here, we combine dual PD-L1 and VEGFA blockade (DPVB) with low-dose radiotherapy (LDRT), which rapidly inflames tumors, rendering them vulnerable to immunotherapy. The combinatorial therapy exhibits superior antitumor efficacy mediated by CD8 + T cells in various preclinical HCC models. Treatment efficacy relies upon mobilizing exhausted-like CD8 + T cells (CD8 + Tex) with effector function and cytolytic capacity. Mechanistically, LDRT sensitizes tumors to DPVB by recruiting stem-like CD8 + Tpex, the progenitor exhausted CD8 + T cells, from draining lymph nodes (dLNs) into the tumor via the CXCL10/CXCR3 axis. Together, these results further support the rationale for combining LDRT with atezolizumab and bevacizumab, and its clinical translation. An increasing number of preclinical and clinical studies have investigated the antitumor efficacy of combined radiotherapy and immunotherapy. Here the authors report that low-dose radiotherapy enhances the antitumor effect of dual VEGFA and PD-L1 blockade in preclinical models of hepatocellular carcinoma.

Although various methods exist for osteoporosis prevention, most patients fail to receive optimal treatment due to information asymmetry between physicians and patients, as well as limited consultation time. Current literatures suggest that decision aids can support clinical decision-making by improving patients' risk perception and treatment acceptance. This scoping review described the use and effectiveness of decision aids in clinical decision-making among individuals with osteoporosis. The review will include studies conducted in various countries that focus on decision-aiding interventions for people with osteoporosis in different settings and are published in English or Chinese. PubMed, CINAHL, Web of Science, Embase, Cochrane Library, China Knowledge Network, Wanfang Database, and China Biomedical Literature Database were searched. The search timeframe was from the establishment of the database to June 30, 2024. Studies that meet the inclusion criteria will be eligible for selection. The process of selecting eligible studies will then be summarized on a PRISMA-ScR chart. Collated in data-extraction tables will be authorship information, publication date, country, study site, sample information, study type, intervention form, content elements, application scope, and outcome indicators. The content elements, application scope, and outcome indicators will be analyzed using a thematic analysis and summarized using a narrative summary. With strong efficacy and viability, DA greatly enhances patients' decision-making experience and decision quality. In order to provide patients with osteoporosis with high-quality decision-making support, it will be necessary to conduct large-scale, randomized controlled studies in the future with the goal of guaranteeing homogeneous interventions, expand the scope and meaning of the application of DA in osteoporosis, improve professional support during the decision-making process, create scientific and useful decision-making aids, and take specific actions.

Metal halide perovskite solar cells have demonstrated a high power conversion efficiency (PCE), and further enhancement of the PCE requires a reduction of the bandgap-voltage offset (WOC) and the non-radiative recombination photovoltage loss (ΔVOC,nr). Here, we report an effective approach for reducing the photovoltage loss through the simultaneous passivation of internal bulk defects and dimensionally graded two-dimensional perovskite interface defects. Through this dimensionally graded perovskite formation approach, an open-circuit voltage (VOC) of 1.24 V was obtained with a champion PCE of 21.54% in a 1.63 eV perovskite system (maximum VOC = 1.25 V, WOC = 0.38 V and ΔVOC,nr = 0.10 V); we further decreased the WOC to 0.326 V in a 1.53 eV perovskite system with a VOC of 1.21 V and a PCE of 23.78% (certified 23.09%). This approach is equally effective in achieving a low WOC (ΔVOC,nr) in 1.56 eV and 1.73 eV perovskite solar cell systems, and further leads to the substantially improved operational stability of perovskite solar cells.The use of a dimensionally graded 2D perovskite interface and passivation results in perovskite solar cells with very low photovoltage loss.