RDBSB: a database for catalytic bioparts with experimental evidence.

Catalytic bioparts are fundamental to the design, construction and optimization of biological systems for specific metabolic pathways. However, the functional characterization information of these bioparts is frequently dispersed across multiple databases and literature sources, posing significant challenges to the effective design and optimization of specific chassis or cell factories. We developed the Registry and Database of Bioparts for Synthetic Biology (RDBSB), a comprehensive resource encompassing 83 193 curated catalytic bioparts with experimental evidences. RDBSB offers their detailed qualitative and quantitative catalytic information, including critical parameters such as activities, substrates, optimal pH and temperature, and chassis specificity. The platform features an interactive search engine, visualization tools and analysis utilities such as biopart finder, structure prediction and pathway design tools. Additionally, RDBSB promotes community engagement through a catalytic bioparts submission system to facilitate rapid data sharing and utilization. To date, RDBSB has supported the contribution of >1000 catalytic bioparts. We anticipate that the database will significantly enhance the resources available for pathway design in synthetic biology and serve essential tools for researchers. RDBSB is freely available at https://www.biosino.org/rdbsb/.

Nanopore-based full-length transcriptome sequencing for understanding the underlying molecular mechanisms of rapid and slow progression of diabetes nephropathy.

BACKGROUND: Diabetic nephropathy (DN) has been a major factor in the outbreak of end-stage renal disease for decades. As the underlying mechanisms of DN development remains unclear, there is no ideal methods for the diagnosis and therapy. OBJECTIVE: We aimed to explore the key genes and pathways that affect the rate progression of DN. METHODS: Nanopore-based full-length transcriptome sequencing was performed with serum samples from DN patients with slow progression (DNSP, n = 5) and rapid progression (DNRP, n = 6). RESULTS: Here, transcriptome proclaimed 22,682 novel transcripts and obtained 45,808 simple sequence repeats, 1,815 transcription factors, 5,993 complete open reading frames, and 1,050 novel lncRNA from the novel transcripts. Moreover, a total of 341 differentially expressed transcripts (DETs) and 456 differentially expressed genes (DEGs) between the DNSP and DNRP groups were identified. Functional analyses showed that DETs mainly involved in ferroptosis-related pathways such as oxidative phosphorylation, iron ion binding, and mitophagy. Moreover, Functional analyses revealed that DEGs mainly involved in oxidative phosphorylation, lipid metabolism, ferroptosis, autophagy/mitophagy, apoptosis/necroptosis pathway. CONCLUSION: Collectively, our study provided a full-length transcriptome data source for the future DN research, and facilitate a deeper understanding of the molecular mechanisms underlying the differences in fast and slow progression of DN.

zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation.

Isobaric labeling-based mass spectrometry (ILMS) has been widely used to quantify, on a proteome-wide scale, the relative protein abundance in different biological conditions. However, large-scale ILMS data sets typically involve multiple runs of mass spectrometry, bringing great computational difficulty to the integration of ILMS samples. We present zMAP, a toolset that makes ILMS intensities comparable across mass spectrometry runs by modeling the associated mean-variance dependence and accordingly applying a variance stabilizing z-transformation. The practical utility of zMAP is demonstrated in several case studies involving the dynamics of cell differentiation and the heterogeneity across cancer patients.

The inoculation of Bacillus paralicheniformis and Streptomyces thermoviolaceus enhances the lignocellulose degradation and microbial communities during spent mushroom substrate composting.

The burgeoning global mushroom industry has precipitated challenges related to the efficient and sustainable utilization of spent mushroom substrate (SMS). Composting is regarded as an efficient way for the ecological utilization of SMS. The addition of microbial inoculants can promote the composting process and improve the quality of compost products. This study introduced two bacterial inoculants, Bacillus paralicheniformis HL-05 (BP) and Streptomyces thermoviolaceus LC-10 (ST), into the composting process of SMS. The impact of these inoculants was evaluated through analyses of physicochemical properties, lignocellulose degradation, and high-throughput sequencing to elucidate their ecological roles and optimize the composting process. The results suggest that inoculation with BP and ST significantly prolonged the thermophilic stage by 2-3 days, representing an increase of 22.22-33.33%. Moreover, it boosted the degradation rates of cellulose, hemicellulose, and lignin by 18.37-29.77%, 35.74-50.43%, and 40.32-40.83%, respectively, compared to the control. Furthermore, inoculation rapidly altered the microbial community structure during the rapid temperature-rising stage and strengthened interconnections among composting microorganisms. The microbial inoculation substantially enhanced the proliferation of thermophilic lignocellulose-degrading microorganisms during the thermophilic stage, thereby facilitating the utilization of lignocellulose. This study proposes a novel and effective strategy for SMS composting using microbial inoculants.

Non-Markovian noise mitigation in quantum teleportation: enhancing fidelity and entanglement.

Maintaining quantum coherence and entanglement in the presence of environmental noise, particularly within non-Markovian contexts, represents a significant challenge for the progression of quantum information science and technology. This study offers a substantial advancement by investigating the dynamics of a two-qubit system subjected to diverse noise conditions, encompassing relaxation, dephasing, and their cumulative effects. By employing quantum-state-diffusion equations specifically crafted for non-Markovian environments, we introduce an innovative strategy to counteract the detrimental influences of environmental noise on quantum teleportation fidelity and entanglement concurrence. Our results underscore the potential for external interventions to markedly improve the resilience of quantum information processing tasks over prolonged durations, especially in settings where dephasing noise prevails. A key revelation is the intricate relationship between dephasing noise and the initial state of entanglement, which profoundly impacts the occurrence of entanglement sudden death. This research not only deepens our comprehension of quantum system dynamics under noisy circumstances but also furnishes practical directives for engineering robust quantum systems, a necessity for the development of scalable quantum technologies.

Based on improved joint detection and tracking of UAV for multi-target detection of livestock.

In agriculture, specifically livestock monitoring, drones' ability to track multiple targets is essential for advancing the field. However, limited computing resources and unpredictable drone movements often cause issues like ambiguous video frames, object obstructions, and size deviations. These inconsistencies reduce tracking accuracy, making traditional algorithms inadequate for handling drone footage. This study introduces an enhanced deep learning-based multi-target drone tracker framework that enables real-time processing. The proposed method combines object detection and tracking by leveraging consecutive frame pairs to extract and share features, enhancing computational efficiency. It employs diverse loss functions to address class and sample distribution imbalances and includes a composite deblurring module to enhance detection accuracy. Object association utilizes a dual regress bounding box technique, aiding in object identification verification and predictive motion. Live tracking is achieved by predicting object locations in subsequent frames, enabling real-time tracking. Evaluation against leading benchmarks shows that the system improves precision and speed, achieving a 4.3 % increase in Multi-Object Tracking Accuracy (MOTA) and a 7.7 % boost in F1 score.

High-risk powered two-wheelers scenarios generation for autonomous vehicle testing using WGAN.

OBJECTIVE: Autonomous vehicles (AVs) have the potential to revolutionize the future of mobility by significantly improving traffic safety. This study presents a novel method for validating the safety performance of AVs in high-risk scenarios involving powered 2-wheelers (PTWs). By generating high-risk scenarios using in-depth crash data, this study is devoted to addressing the challenge of public road scenarios in testing, which often lack the necessary complexity and risk to effectively evaluate the capabilities of AVs in high-risk situations. METHOD: Our approach employs a Wasserstein generative adversarial network (WGAN) to generate high-risk scenes, particularly focusing on PTW scenarios. By extracting 314 car-to-PTW crashes from the China In-depth Mobility Safety Study-Traffic Accident database, we simulate outcomes using PC-Crash software. The data are divided into scenes at 0.1-s intervals, with WGAN generating numerous high-risk scenes. By using a cumulative distribution function (CDF), we sampled and analyzed the vehicle's dynamic information to generate complete scenarios applicable to the test. The validation process involves using the SVL Simulator and the Baidu Apollo joint simulation platform to evaluate the AV's driving behavior and interactions with PTWs. RESULTS: This study evaluates model generation results by comparing distributions using Wasserstein distance as an indicator. The generator converges after approximately 200 epochs, with the iterator converging quickly. Subsequently, 10,000 new scenes are then generated. The distribution of several key parameters in the generated scenes can be found to approximate that of the original scenes. After sampling, the usability of generated scenarios is 64.76%. Virtual simulations confirm the effectiveness of the scenario generation method, with a generated scenario crash rate of 16.50% closely reflecting the original rate of 15.0%, showcasing the method's capacity to produce realistic and hazardous scenarios. CONCLUSIONS: The experimental results suggest that these scenarios exhibit a level of risk similar to the original crashes and are effective for testing AVs. Consequently, the generated scenarios enhance the diversity of the scenario library and accelerate the overall testing process of AVs.

CPMKG: a condition-based knowledge graph for precision medicine.

Personalized medicine tailors treatments and dosages based on a patient's unique characteristics, particularly its genetic profile. Over the decades, stratified research and clinical trials have uncovered crucial drug-related information-such as dosage, effectiveness, and side effects-affecting specific individuals with particular genetic backgrounds. This genetic-specific knowledge, characterized by complex multirelationships and conditions, cannot be adequately represented or stored in conventional knowledge systems. To address these challenges, we developed CPMKG, a condition-based platform that enables comprehensive knowledge representation. Through information extraction and meticulous curation, we compiled 307 614 knowledge entries, encompassing thousands of drugs, diseases, phenotypes (complications/side effects), genes, and genomic variations across four key categories: drug side effects, drug sensitivity, drug mechanisms, and drug indications. CPMKG facilitates drug-centric exploration and enables condition-based multiknowledge inference, accelerating knowledge discovery through three pivotal applications. To enhance user experience, we seamlessly integrated a sophisticated large language model that provides textual interpretations for each subgraph, bridging the gap between structured graphs and language expressions. With its comprehensive knowledge graph and user-centric applications, CPMKG serves as a valuable resource for clinical research, offering drug information tailored to personalized genetic profiles, syndromes, and phenotypes. Database URL: https://www.biosino.org/cpmkg/.

Balancing thermodynamic stability, dynamics, and kinetics in phase separation of intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs) are prevalent participants in liquid-liquid phase separation due to their inherent potential for promoting multivalent binding. Understanding the underlying mechanisms of phase separation is challenging, as phase separation is a complex process, involving numerous molecules and various types of interactions. Here, we used a simplified coarse-grained model of IDPs to investigate the thermodynamic stability of the dense phase, conformational properties of IDPs, chain dynamics, and kinetic rates of forming condensates. We focused on the IDP system, in which the oppositely charged IDPs are maximally segregated, inherently possessing a high propensity for phase separation. By varying interaction strengths, salt concentrations, and temperatures, we observed that IDPs in the dense phase exhibited highly conserved conformational characteristics, which are more extended than those in the dilute phase. Although the chain motions and global conformational dynamics of IDPs in the condensates are slow due to the high viscosity, local chain flexibility at the short timescales is largely preserved with respect to that at the free state. Strikingly, we observed a non-monotonic relationship between interaction strengths and kinetic rates for forming condensates. As strong interactions of IDPs result in high stable condensates, our results suggest that the thermodynamics and kinetics of phase separation are decoupled and optimized by the speed-stability balance through underlying molecular interactions. Our findings contribute to the molecular-level understanding of phase separation and offer valuable insights into the developments of engineering strategies for precise regulation of biomolecular condensates.

Risk factors for unplanned intensive care unit admission after esophagectomy: a retrospective cohort study of 628 patients with esophageal cancer.

Introduction: Esophagectomy patients who experience unplanned ICU admission (UIA) may experience a heavier economic burden and worse clinical outcomes than those who experience routine intensive care unit (ICU) admission. The aim of this study was to identify the risk factors for postoperative UIA in patients who underwent esophagectomy. Methods: We retrospectively included patients with esophageal cancer who underwent esophagectomy. The characteristics of postoperative UIA were described, and univariable and multivariable analyses were performed based on the logistic regression model. Furthermore, a recursive partitioning analysis was adopted to stratify the patients according to the risk of UIA. Results: A total of 628 patients were included in our final analysis, among whom 57 (9.1%) had an UIA. The patients in the UIA cohort had a higher rate of in-hospital mortality (P<0.001), longer hospital stay (P<0.001), and higher associated costs (P<0.001). Multivariable analysis showed that hybrid/open esophagectomy (OR=4.366, 95% CI=2.142 to 8.897, P<0.001), operation time (OR=1.006, 95% CI=1.002 to 1.011, P=0.007), intraoperative blood transfusion (OR=3.118, 95% CI=1.249 to 7.784, P=0.015) and the prognostic nutrition index (PNI) (OR=0.779, 95% CI=0.724 to 0.838, P<0.001) were independently associated with UIA. Conclusions: We identified several critical independent perioperative risk factors that may increase the risk of UIA following esophagectomy, and the above risk factors should be the focus of attention to reduce the incidence of postoperative UIA.

A 70-Year-Old Man With an Encapsulated Mediastinal Fluid Collection.

CASE PRESENTATION: A 70-year-old man was diagnosed with mid-thoracic esophageal squamous cell carcinoma (distance from incisors, 27-30 cm) because of progressive dysphagia and underwent thoracic laparoscopic esophagectomy at a local hospital. He was transferred from the ICU 4 days after surgery; however, a large amount of purulent fluid exuded from the neck incision after oral drinking, which was consistent with cervical anastomotic leakage. Later, the patient experienced difficulty breathing and expelling sputum; he was then transferred back to the ICU for treatment. A CT scan showed massive fluid collection in the mediastinum and left pleural cavity. Thoracentesis yielded yellowish fluid, and the patient's general condition gradually improved after placement of a closed chest drainage system. The patient's cervical anastomotic fistula persisted and did not heal, and he was subsequently transferred to our medical center with the closed chest drainage system left in place.

The relationship between tricuspid annular plane systolic excursion on transesophageal echocardiography and the incidence of postoperative acute kidney injury in patients undergoing coronary artery bypass grafting surgery: a multicenter prospective cohort study.

BACKGROUND: To date, the relationship between the Transesophageal Echocardiography (TEE) monitoring indicator tricuspid annular plane systolic excursion (TAPSE) and the incidence of postoperative acute kidney injury (AKI) in Coronary Artery Bypass Grafting(CABG) patients remains unknown. The main objective of this study was to explore the relationship between the TAPSE and the incidence of AKI in CABG patients. METHODS: This was a multicenter prospective cohort study was conducted between September 2021 and July 2022. Among 266 patients aged at least 18 years who underwent elective CABG, 140 were included. RESULTS: We measured TAPSE via M-mode TEE via the mid-esophageal (ME) right ventricle(RV) inflow-outflow view (60°). All echocardiographic measurements were performed three separate times at each time point: T0 (before the start of CABG), T2 (approximately 5 ∼ 10 min after neutralization of protamine) and T3 (before leaving the operating room), and then averaged. Serum creatinine was measured 1 day before and within 7 days after CABG. There was no statistically significant association between the TEE-monitoring indicator TAPSE and the incidence of postoperative AKI in patients who underwent CABG. CONCLUSIONS: The TAPSE was not significantly correlated with postoperative AKI incidence and could not predict the early occurrence of postoperative AKI in CABG patients. TEE needs more evaluation for clinical efficacy of predicting the early occurrence of postoperative AKI in isolated CABG.

The diversity and biogeography of bacterial communities in lake sediments across different climate zones.

Bacteria are diverse and play important roles in biogeochemical cycling of aquatic ecosystems, but the global distribution patterns of bacterial communities in lake sediments across different climate zones are still obscure. Here we integrated the high-throughput sequencing data of 750 sediment samples from published literature to investigate the distribution of bacterial communities in different climate zones and the potential driving mechanisms. The obtained results indicated that the diversity and richness of bacterial community were notably higher in temperate and cold zones than those in other climate zones. In addition, the bacterial community composition varied significantly in different climate zones, which further led to changes in bacterial functional groups. Specifically, the relative abundance of nitrogen cycling functional groups in polar zones was notably higher compared to other climate zones. Regression analysis revealed that climate (mean annual precipitation, MAP; and mean annual temperature, MAT), vegetation, and geography together determined the diversity pattern of sediment bacterial community on a global scale. The results of partial least squares path modeling further demonstrated that climate was the most significant factor affecting the composition and diversity of bacterial communities, and MAP was the most important climate factor affecting the composition of bacteria community (R2 = 0.443, P < 0.001). It is worth noting that a strong positive correlation was observed between the abundance of the dominant bacterial group uncultured_f_Anaerolineaceae and the normalized difference vegetation index (NDVI; P < 0.001), suggesting that vegetation could affect bacterial community diversity by influencing dominant bacterial taxa. This study enhances our understanding of the global diversity patterns and biogeography of sediment bacteria.

Optimizing wheat prosperity: innovative drip irrigation and nitrogen management strategies for enhanced yield and quality of winter wheat in the Huang-Huai-Hai region.

Introduction: To examine the impacts of varied water and nitroge combinations on wheat yield and quality under drip irrigation in the Huang-Huai-Hai area, a field experiment was conducted over two growing seasons of winter wheat from 2019 to 2021. Methods: Traditional irrigation and fertilization methods served as the control (CK), with two nitrogen application rates set: N1 (180 kg/ha) and N2 (210 kg/ha). The irrigation schedules were differentiated by growth stages: jointing, anthesis (S2); jointing, anthesis, and filling (S3); and jointing, booting, anthesis, and filling (S4), at soil depths of 0-10 cm (M1) and 0-20 cm (M2). Results: Results indicated that compared to CK, the 3 and 4 times irrigation treatments comprehensively improved grain yield (GY) by 8.0% and 13.6% respectively, increased the average plant partial factor productivity of nitrogen fertilizer (PFPN) and irrigation use efficiency (IUE) by 57.5% and 38.2%, and 62.2% and 35.8%, respectively. The gluten content (GC) of 3 irrigations was 1.6% higher than CK, and other metrics such as dough tenacity (DT), softness (ST), water absorption (WAS), and gluten hardness (GH) also showed improvements. Furthermore, the contents of amylose, amylopectin, and total starch under 3 irrigations significantly increased by 9.4%, 11.4%, and 9.8%, respectively, with higher than 4 irrigations. The crude protein content and soluble sugar content in 3 irrigations rose by 6.5% and 9.8% respectively over two years. These irrigation treatments also optimized gelatinization characteristics of grains, such as breakdown viscosity (BDV), consistency peak viscosity (CPV), consistency setback viscosity (CSV), pasting temperature (PeT), and pasting time (PaT). Discussion: The study demonstrated that appropriate drip irrigation can effectively synchronize water and nitrogen supply during critical growth stages in winter wheat, ensuring robust late-stage development and efficient transfer of photosynthetic products into the grains, thus enhancing grain mass and yield. This also led to improved utilization of water and fertilizer and enhanced the nutritional and processing quality of the grain. However, excessive irrigation did not further improve grain quality. In conclusion, given the goals of saving water and fertilizer, achieving excellent yield, and ensuring high quality, the N1S3M1 treatment is recommended as an effective production management strategy in the Huang-Huai Hai area; N1S3M2 could be considered in years of water scarcity.

Characterization of Pore Structure and Fluid Mobility of Shale Reservoirs.

Accompanying the commercial exploitation of shale oil and gas in North America, shale oil has gradually become an important resource, sparking great interest among countries around the world in recent years. In this study, focusing on the Paleogene Shahejie Formation in Bohai Bay (Eastern China), techniques such as CT, nitrogen adsorption, mercury injection capillary pressure (MICP), and nuclear magnetic resonance (NMR) were used to characterize the pore structure and mobility of the shale reservoir. Based on the X-ray CT data, the pore radius of the shale reservoir is in the range 0.5-65 µm, and the pore coordination number is concentrated in the range of 1-4. The shale reservoir is poorly connected. The minimum size of the unit body for establishing the digital core model is 380 µm. Based on the experimental data of nitrogen adsorption and MICP, the pores of shale in the study area are mainly classified as ink-bottle-shaped pores, transition-shaped pores, and flat plate slit-shaped pores. The specific surface area and volume of pores are mainly attributed to meso- and macropores. The movable fluid saturation of shale is distributed from 23.59 to 44.42%, the pore throat radius is distributed from 0.001 to 6 µm, and the lower limit of the movable pore throat radius of shale is distributed between 9.0 and 20.1 nm. The movable fluid porosity is mainly distributed between 0.84 and 4.08%, with an average movable fluid porosity of 2.37%. The findings provide a theoretical basis for the efficient development of shale oil resources.

A deep learning-based method enables the automatic and accurate assembly of chromosome-level genomes.

The application of high-throughput chromosome conformation capture (Hi-C) technology enables the construction of chromosome-level assemblies. However, the correction of errors and the anchoring of sequences to chromosomes in the assembly remain significant challenges. In this study, we developed a deep learning-based method, AutoHiC, to address the challenges in chromosome-level genome assembly by enhancing contiguity and accuracy. Conventional Hi-C-aided scaffolding often requires manual refinement, but AutoHiC instead utilizes Hi-C data for automated workflows and iterative error correction. When trained on data from 300+ species, AutoHiC demonstrated a robust average error detection accuracy exceeding 90%. The benchmarking results confirmed its significant impact on genome contiguity and error correction. The innovative approach and comprehensive results of AutoHiC constitute a breakthrough in automated error detection, promising more accurate genome assemblies for advancing genomics research.

Integration of multi-omics reveals the important role of the BBS10 gene in reproduction.

Blood samples are easily obtained from sheep. Therefore, blood analysis can be a convenient method for evaluating reproductive traits in sheep by detecting genetic and metabolic changes in the ovary. By combining 167 RNA sequencing (RNA-seq) data and 60 untargeted metabolomics data, this study analyzed the relationship between genes and metabolites in the ovary and blood. The conjoint KEGG enrichment analysis enriched glutathione metabolic pathways both in the ovary and blood. This finding provides an explanation for possible glutathione metabolic processes in the ovary with metabolite exchange in the blood. The metabolite-gene-disease interaction network revealed a correlation between the expression of certain Bardet-Biedl syndrome (BBS) family genes in the ovary and blood. This indicates that BBS family genes, such as BBS10 in sheep blood, could be a potential biomarker for BBS. We investigated the relationship between BBS10 gene expression in the ovary and lambing numbers using whole-genome sequencing data from 450 ewes. Our findings suggest that g.112314188C > G may lead to decreased litter size in ewes carrying the FecB gene. These SNPs could be potential molecular markers for breeding sheep.

Environmental exposure to cadmium induces olfactory neurotoxicity in fire ants and the molecular basis.

Cadmium (Cd) exhibits widely olfactory toxicity to animals. We previously reported that Cd exposure induces the transcriptional dysregulation of olfactory marker proteins (OMPs) of the red imported fire ant Solenopsis invicta. However, it is still unclear how environmental Cd exposure-induced deregulation of OMPs affects the olfactory signal transduction and olfaction-driven social behavior of S. invicta. Here, we showed that S. invicta displayed dull sensory perception on bait in Cd-contaminated areas and dietary Cd ingestion by S. invicta reduced the bait search efficiency. We hypothesize that deregulation of OMPs by Cd exposure blocks the olfactory signal transduction in fire ants. Our results indicated the odor binding protein 14 (SiOBP14) was consistently inhibited in antennal sensilla of fire ants across Cd exposure at 0.5, 5 and 50 mg/kg. Function analysis in vitro and in vivo demonstrated that SiOBP14 is essential in perception of S. invicta to bait odorants. Cd-exposed fire ants showed weak odorant receptor neurons (ORNs) chemosensory signaling and electroantennogram (EAG) response. Moreover, Cd exposure repeals the preference of S. invicta to the active bait odorants, including 2-methyltetrahydrofuran-3-one, 2-methyl-3-furanthiol and 4,5-dimethylthiazole, and even triggers a behavioral transition from preference to repellence. These results indicate that Cd exposure inhibits the specific OMP expression and disrupts olfactory signal transduction, thereby inducing dull sensory perception of S. invicta to bait odorants. The findings provide new implications for monitoring and control of agricultural insect pests in heavy metal polluted areas.

Iron-Catalyzed Primary Amination of C(sp3)-H Bonds.

Primary amines are privileged molecules in drug development. Yet, there is a noticeable scarcity of methods for directly introducing a primary amine group into the ubiquitous C(sp3)-H bonds within organic compounds. Here, we report an iron-based catalytic system that enables direct primary amination of C(sp3)-H bonds under aqueous conditions and air. Various types of C(sp3)-H bonds, including benzylic, allylic, and aliphatic ones, can be readily functionalized with high selectivity and efficiency. The broad utility of this method has been further verified by late-stage amination of 11 complex bioactive molecules. Mechanistic studies unveil a protonated iron-nitrene complex as the key intermediate for the C-H bond activation. This work extends the toolbox for direct C(sp3)-H functionalizations, opening up new opportunities for late-stage modifications of organic molecules.