Domain Adaptive Code Completion via Language Models and Decoupled Domain Databases

Large Language Models (LLMs) have demonstrated remarkable performance in code completion. However, due to the lack of domain-specific knowledge, they may not be optimal in completing code that requires intensive domain knowledge for example completing the library names. Although there are several works that have confirmed the effectiveness of fine-tuning techniques to adapt language models for code completion in specific domains. They are limited by the need for constant fine-tuning of the model when the project is in constant iteration. To address this limitation, in this paper, we propose $k$NM-LM, a retrieval-augmented language model (R-LM), that integrates domain knowledge into language models without fine-tuning. Different from previous techniques, our approach is able to automatically adapt to different language models and domains. Specifically, it utilizes the in-domain code to build the retrieval-based database decoupled from LM, and then combines it with LM through Bayesian inference to complete the code. The extensive experiments on the completion of intra-project and intra-scenario have confirmed that $k$NM-LM brings about appreciable enhancements when compared to CodeGPT and UnixCoder. A deep analysis of our tool including the responding speed, storage usage, specific type code completion, and API invocation completion has confirmed that $k$NM-LM provides satisfactory performance, which renders it highly appropriate for domain adaptive code completion. Furthermore, our approach operates without the requirement for direct access to the language model's parameters. As a result, it can seamlessly integrate with black-box code completion models, making it easy to integrate our approach as a plugin to further enhance the performance of these models.Comment: Accepted by ASE202

Berberine produces antidepressant-like effects in ovariectomized mice

Berberine has been reports to have antidepressant-like effects. However, it is seldom known whether berberine produces antidepressant-like effects in ovariectomized mice, which exhibit depressive-like responses. To examine the antidepressant-like effects of berberine in ovariectomized mice, behavioral tests were conducted, including the forced swimming test and the open field test. To elucidate the mechanisms, levels of BDNF, phosphorylated CREB and phosphorylated eEF2 were analyzed by western blotting, and c-Fos induction was examined by immunohistochemistry. In the forced swimming test, berberine decreased the immobility time in a dose-dependent manner, reversing the depressive-like effect observed in ovariectomized mice, and this effect was blocked by the 5-HT2 antagonist ketanserin. In addition, western blotting indicated that BDNF and peEF2 in the hippocampus, but not pCREB/CREB in the frontal cortex, were affected by berberine treatment. Furthermore, immunohistochemistry demonstrated that the reduction in c-Fos induced by ovariectomy were greater after berberine treatment. Ketanserin also antagonized the effect of berberine on the c-Fos expression. Our findings suggest that berberine exerts antidepressant-like effects in ovariectomized mice, and 5-HT2 receptor activation may be partially related to the antidepressant-like effects of the berberine by BDNF-CREB and eEF2 pathways

Practical Program Repair via Preference-based Ensemble Strategy

peer reviewedTo date, over 40 Automated Program Repair (APR) tools have been designed with varying bug-fixing strategies, which have been demonstrated to have complementary performance in terms of being effective for different bug classes. Intuitively, it should be feasible to improve the overall bug-fixing performance of APR via assembling existing tools. Unfortunately, simply invoking all available APR tools for a given bug can result in unacceptable costs on APR execution as well as on patch validation (via expensive testing). Therefore, while assembling existing tools is appealing, it requires an efficient strategy to reconcile the need to fix more bugs and the requirements for practicality. In light of this problem, we propose a Preference-based Ensemble Program Repair framework (P-EPR), which seeks to effectively rank APR tools for repairing different bugs. P-EPR is the first non-learning-based APR ensemble method that is novel in its exploitation of repair patterns as a major source of knowledge for ranking APR tools and its reliance on a dynamic update strategy that enables it to immediately exploit and benefit from newly derived repair results. Experimental results show that P-EPR outperforms existing strategies significantly both in flexibility and effectiveness

Theranostic Quercetin Nanoparticle for Treatment of Hepatic Fibrosis.

The progression of hepatic fibrosis can lead to cirrhosis and hepatic failure, but the development of antifibrotic drugs have faced the challenges of poor effectiveness and targeted specificity. Herein, a theranostic strategy was carried to encapsulate a natural medicine (Quercetin, QR) into hepatitis B core (HBc) protein nanocages (NCs) for imaging and targeted treatment of hepatic fibrosis. It was noted that nanoparticles (RGD-HBc/QR) with surface-displayed RGD targeting ligand exhibit a rather high selectivity toward activated HSCs via the binding affinity with integrin αvβ3, and an efficient inhibition of proliferation and activation of hepatic stellate cells (HSCs) in vitro and in vivo. Once encapsulated in quercetin-gadolinium complex and/or labeled with the NIR fluorescent probes (Cy5.5), the resulting nanoparticles (RGD-HBc/QGd) show great potential as NIR fluorescent and magnetic resonance imaging contrast agents for hepatic fibrosis in vivo. Therefore, the multifunctional integrin-targeted nanoparticles could selectively deliver QR to the activated HSCs, and may provide an effective antifibrotic theranostic strategy

Highly Efficient Modular Construction of Functional Drug Delivery Platform Based on Amphiphilic Biodegradable Polymers via Click Chemistry

Amphiphilic copolymers with pendant functional groups in polyester segments are widely used in nanomedicine. These enriched functionalities are designed to form covalent conjugates with payloads or provide additional stabilization effects for encapsulated drugs. A general method is successfully developed for the efficient preparation of functional biodegradable PEG-polyester copolymers via click chemistry. Firstly, in the presence of mPEG as initiator, Sn(Oct)2-catalyzed ring-opening polymerization of the α-alkynyl functionalized lactone with D,L-lactide or ε-caprolactone afforded linear mPEG-polyesters bearing multiple pendant alkynyl groups. Kinetic studies indicated the formation of random copolymers. Through copper-catalyzed azide-alkyne cycloaddition reaction, various small azido molecules with different functionalities to polyester segments are efficiently grafted. The molecular weights, polydispersities and grafting efficiencies of azido molecules of these copolymers were investigated by NMR and GPC. Secondly, it is demonstrated that the resulting amphiphilic functional copolymers with low CMC values could self-assemble to form nanoparticles in aqueous media. In addition, the in vitro degradation study and cytotoxicity assays indicated the excellent biodegradability and low cytotoxicity of these copolymers. This work provides a general approach toward the preparation of functional PEG-polyester copolymers in a quite efficient way, which may further facilitate the application of functional PEG-polyesters as drug delivery materials

Inhalation treatment of primary lung cancer using liposomal curcumin dry powder inhalers

Lung cancer is the leading cause of cancer-related deaths. Traditional chemotherapy causes serious toxicity due to the wide bodily distribution of these drugs. Curcumin is a potential anticancer agent but its low water solubility, poor bioavailability and rapid metabolism significantly limits clinical applications. Here we developed a liposomal curcumin dry powder inhaler (LCD) for inhalation treatment of primary lung cancer. LCDs were obtained from curcumin liposomes after freeze-drying. The LCDs had a mass mean aerodynamic diameter of 5.81 μm and a fine particle fraction of 46.71%, suitable for pulmonary delivery. The uptake of curcumin liposomes by human lung cancer A549 cells was markedly greater and faster than that of free curcumin. The high cytotoxicity on A549 cells and the low cytotoxicity of curcumin liposomes on normal human bronchial BEAS-2B epithelial cells yielded a high selection index partly due to increased cell apoptosis. Curcumin powders, LCDs and gemcitabine were directly sprayed into the lungs of rats with lung cancer through the trachea. LCDs showed higher anticancer effects than the other two medications with regard to pathology and the expression of many cancer-related markers including VEGF, malondialdehyde, TNF-α, caspase-3 and BCL-2. LCDs are a promising medication for inhalation treatment of lung cancer with high therapeutic efficiency. Key words: Curcumin, Dry powder inhaler, Liposome, Primary lung cancer, Pulmonary deliver

Numerical investigation on the clogging-collapsing events in granular discharge

Granular flow in hoppers is widely encountered in industries and daily life. Despite its ubiquity, understanding on its basic flow behavior is still limited. Typically, the flow may be interrupted by the formation of arches and the phase transition ensues, and in general these arches may not collapse without external energy input such as vibration. However, in this study, the rare events of granular flow arrested by the formation of unstable arches and then restarted by their spontaneous collapsing, or the clogging-collapsing events, were observed in both lab experiments and numerical simulations in the discrete element method (DEM). It was demonstrated that the clogging may result from the coordinated evolution of the entire force chain system and the kinetic energy dissipated incompletely in bulk is mainly responsible for the collapsing. The evolution of the kinetic energy displays different modes in the clogging-collapsing , permanent clogging events, suggesting that the collapsing can be predicted by monitoring the variance of the kinetic energy

The Role of Neural Plasticity in Depression: From Hippocampus to Prefrontal Cortex

Neural plasticity, a fundamental mechanism of neuronal adaptation, is disrupted in depression. The changes in neural plasticity induced by stress and other negative stimuli play a significant role in the onset and development of depression. Antidepressant treatments have also been found to exert their antidepressant effects through regulatory effects on neural plasticity. However, the detailed mechanisms of neural plasticity in depression still remain unclear. Therefore, in this review, we summarize the recent literature to elaborate the possible mechanistic role of neural plasticity in depression. Taken together, these findings may pave the way for future progress in neural plasticity studies

Numerical investigation on the clogging-collapsing events in granular discharge

Granular flow in hoppers is widely encountered in industries and daily life. Despite its ubiquity, understanding on its basic flow behavior is still limited. Typically, the flow may be interrupted by the formation of arches and the phase transition ensues, and in general these arches may not collapse without external energy input such as vibration. However, in this study, the rare events of granular flow arrested by the formation of unstable arches and then restarted by their spontaneous collapsing, or the clogging-collapsing events, were observed in both lab experiments and numerical simulations in the discrete element method (DEM). It was demonstrated that the clogging may result from the coordinated evolution of the entire force chain system and the kinetic energy dissipated incompletely in bulk is mainly responsible for the collapsing. The evolution of the kinetic energy displays different modes in the clogging-collapsing , permanent clogging events, suggesting that the collapsing can be predicted by monitoring the variance of the kinetic energy