Human iPSC 4R tauopathy model uncovers modifiers of tau propagation.

Tauopathies are age-associated neurodegenerative diseases whose mechanistic underpinnings remain elusive, partially due to a lack of appropriate human models. Here, we engineered human induced pluripotent stem cell (hiPSC)-derived neuronal lines to express 4R Tau and 4R Tau carrying the P301S MAPT mutation when differentiated into neurons. 4R-P301S neurons display progressive Tau inclusions upon seeding with Tau fibrils and recapitulate features of tauopathy phenotypes including shared transcriptomic signatures, autophagic body accumulation, and reduced neuronal activity. A CRISPRi screen of genes associated with Tau pathobiology identified over 500 genetic modifiers of seeding-induced Tau propagation, including retromer VPS29 and genes in the UFMylation cascade. In progressive supranuclear palsy (PSP) and Alzheimer's Disease (AD) brains, the UFMylation cascade is altered in neurofibrillary-tangle-bearing neurons. Inhibiting the UFMylation cascade in vitro and in vivo suppressed seeding-induced Tau propagation. This model provides a robust platform to identify novel therapeutic strategies for 4R tauopathy.

Tau interactome maps synaptic and mitochondrial processes associated with neurodegeneration.

Tau (MAPT) drives neuronal dysfunction in Alzheimer disease (AD) and other tauopathies. To dissect the underlying mechanisms, we combined an engineered ascorbic acid peroxidase (APEX) approach with quantitative affinity purification mass spectrometry (AP-MS) followed by proximity ligation assay (PLA) to characterize Tau interactomes modified by neuronal activity and mutations that cause frontotemporal dementia (FTD) in human induced pluripotent stem cell (iPSC)-derived neurons. We established interactions of Tau with presynaptic vesicle proteins during activity-dependent Tau secretion and mapped the Tau-binding sites to the cytosolic domains of integral synaptic vesicle proteins. We showed that FTD mutations impair bioenergetics and markedly diminished Tau's interaction with mitochondria proteins, which were downregulated in AD brains of multiple cohorts and correlated with disease severity. These multimodal and dynamic Tau interactomes with exquisite spatial resolution shed light on Tau's role in neuronal function and disease and highlight potential therapeutic targets to block Tau-mediated pathogenesis.

Neuropeptide delivery to synapses by long-range vesicle circulation and sporadic capture.

Neurotransmission requires anterograde axonal transport of dense core vesicles (DCVs) containing neuropeptides and active zone components from the soma to nerve terminals. However, it is puzzling how one-way traffic could uniformly supply sequential release sites called en passant boutons. Here, Drosophila neuropeptide-containing DCVs are tracked in vivo for minutes with a new method called simultaneous photobleaching and imaging (SPAIM). Surprisingly, anterograde DCVs typically bypass proximal boutons to accumulate initially in the most distal bouton. Then, excess distal DCVs undergo dynactin-dependent retrograde transport back through proximal boutons into the axon. Just before re-entering the soma, DCVs again reverse for another round of anterograde axonal transport. While circulating over long distances, both anterograde and retrograde DCVs are captured sporadically in en passant boutons. Therefore, vesicle circulation, which includes long-range retrograde transport and inefficient bidirectional capture, overcomes the limitations of one-way anterograde transport to uniformly supply release sites with DCVs.

Does vaping increase the likelihood of SARS-CoV-2 infection? Paradoxically yes and no.

Data on the relationship between electronic cigarettes (ECs) and SARS-CoV-2 infection are limited and contradictory. Our objectives were to investigate the impact of EC aerosols on SARS-CoV-2 infection of human bronchial epithelial cells and identify the causative chemical(s). Fully differentiated human bronchial epithelial tissues (hBETs) were exposed at the air-liquid interface (ALI) to aerosols produced from JUUL "Virginia Tobacco" and BLU ECs, as well as nicotine, propylene glycol (PG), vegetable glycerin (VG), and benzoic acid, and infection was then evaluated with SARS-CoV-2 pseudoparticles. Pseudoparticle infection of hBETs increased with aerosols produced from PG/VG, PG/VG plus nicotine, or BLU ECs; however, JUUL EC aerosols did not increase infection compared with controls. Increased infection in PG/VG alone was due to enhanced endocytosis, whereas increased infection in PG/VG plus nicotine or in BLU ECs was caused by nicotine-induced elevation of the aerosol's pH, which correlated with increased transmembrane protease, serine 2 (TMPRSS2) activity. Notably, benzoic acid in JUUL aerosols mitigated the enhanced infection caused by PG/VG or nicotine, offering protection that lasted for at least 48 h after exposure. In conclusion, the study demonstrates that EC aerosols can impact susceptibility to SARS-CoV-2 infection depending on their specific ingredients. PG/VG alone or PG/VG plus nicotine enhanced infection through different mechanisms, whereas benzoic acid in JUUL aerosols mitigated the increased infection caused by certain ingredients. These findings highlight the complex relationship between ECs and SARS-CoV-2 susceptibility, emphasizing the importance of considering the specific aerosol ingredients when evaluating the potential effects of ECs on infection risk.NEW & NOTEWORTHY Data on the relationship between electronic cigarettes (ECs) and SARS-CoV-2 infection are limited and contradictory. We investigated the impact of EC aerosols and their ingredients on SARS-CoV-2 infection of human bronchial epithelial cells. Our data show that specific ingredients in EC aerosols impact the susceptibility to SARS-CoV-2 infection. Propylene glycol (PG)/vegetable glycerin (VG) alone or PG/VG plus nicotine enhanced infection through different mechanisms, whereas benzoic acid in JUUL aerosols mitigated the increased infection caused by these ingredients.

Improving bulk RNA-seq classification by transferring gene signature from single cells in acute myeloid leukemia.

The advances in single-cell RNA sequencing (scRNA-seq) technologies enable the characterization of transcriptomic profiles at the cellular level and demonstrate great promise in bulk sample analysis thereby offering opportunities to transfer gene signature from scRNA-seq to bulk data. However, the gene expression signatures identified from single cells are typically inapplicable to bulk RNA-seq data due to the profiling differences of distinct sequencing technologies. Here, we propose single-cell pair-wise gene expression (scPAGE), a novel method to develop single-cell gene pair signatures (scGPSs) that were beneficial to bulk RNA-seq classification to transfer knowledge across platforms. PAGE was adopted to tackle the challenge of profiling differences. We applied the method to acute myeloid leukemia (AML) and identified the scGPS from mouse scRNA-seq that allowed discriminating between AML and control cells. The scGPS was validated in bulk RNA-seq datasets and demonstrated better performance (average area under the curve [AUC] = 0.96) than the conventional gene expression strategies (average AUC$\le$ 0.88) suggesting its potential in disclosing the molecular mechanism of AML. The scGPS also outperformed its bulk counterpart, which highlighted the benefit of gene signature transfer. Furthermore, we confirmed the utility of scPAGE in sepsis as an example of other disease scenarios. scPAGE leveraged the advantages of single-cell profiles to enhance the analysis of bulk samples revealing great potential of transferring knowledge from single-cell to bulk transcriptome studies.

Deciphering associations between gut microbiota and clinical factors using microbial modules.

MOTIVATION: Human gut microbiota plays a vital role in maintaining body health. The dysbiosis of gut microbiota is associated with a variety of diseases. It is critical to uncover the associations between gut microbiota and disease states as well as other intrinsic or environmental factors. However, inferring alterations of individual microbial taxa based on relative abundance data likely leads to false associations and conflicting discoveries in different studies. Moreover, the effects of underlying factors and microbe-microbe interactions could lead to the alteration of larger sets of taxa. It might be more robust to investigate gut microbiota using groups of related taxa instead of the composition of individual taxa. RESULTS: We proposed a novel method to identify underlying microbial modules, i.e. groups of taxa with similar abundance patterns affected by a common latent factor, from longitudinal gut microbiota and applied it to inflammatory bowel disease (IBD). The identified modules demonstrated closer intragroup relationships, indicating potential microbe-microbe interactions and influences of underlying factors. Associations between the modules and several clinical factors were investigated, especially disease states. The IBD-associated modules performed better in stratifying the subjects compared with the relative abundance of individual taxa. The modules were further validated in external cohorts, demonstrating the efficacy of the proposed method in identifying general and robust microbial modules. The study reveals the benefit of considering the ecological effects in gut microbiota analysis and the great promise of linking clinical factors with underlying microbial modules. AVAILABILITY AND IMPLEMENTATION: https://github.com/rwang-z/microbial_module.git.

bvnGPS: a generalizable diagnostic model for acute bacterial and viral infection using integrative host transcriptomics and pretrained neural networks.

MOTIVATION: The confusion of acute inflammation infected by virus and bacteria or noninfectious inflammation will lead to missing the best therapy occasion resulting in poor prognoses. The diagnostic model based on host gene expression has been widely used to diagnose acute infections, but the clinical usage was hindered by the capability across different samples and cohorts due to the small sample size for signature training and discovery. RESULTS: Here, we construct a large-scale dataset integrating multiple host transcriptomic data and analyze it using a sophisticated strategy which removes batch effect and extracts the common information from different cohorts based on the relative expression alteration of gene pairs. We assemble 2680 samples across 16 cohorts and separately build gene pair signature (GPS) for bacterial, viral, and noninfected patients. The three GPSs are further assembled into an antibiotic decision model (bacterial-viral-noninfected GPS, bvnGPS) using multiclass neural networks, which is able to determine whether a patient is bacterial infected, viral infected, or noninfected. bvnGPS can distinguish bacterial infection with area under the receiver operating characteristic curve (AUC) of 0.953 (95% confidence interval, 0.948-0.958) and viral infection with AUC of 0.956 (0.951-0.961) in the test set (N = 760). In the validation set (N = 147), bvnGPS also shows strong performance by attaining an AUC of 0.988 (0.978-0.998) on bacterial-versus-other and an AUC of 0.994 (0.984-1.000) on viral-versus-other. bvnGPS has the potential to be used in clinical practice and the proposed procedure provides insight into data integration, feature selection and multiclass classification for host transcriptomics data. AVAILABILITY AND IMPLEMENTATION: The codes implementing bvnGPS are available at https://github.com/Ritchiegit/bvnGPS. The construction of iPAGE algorithm and the training of neural network was conducted on Python 3.7 with Scikit-learn 0.24.1 and PyTorch 1.7. The visualization of the results was implemented on R 4.2, Python 3.7, and Matplotlib 3.3.4.

Exploring the phylogeny and depth evolution of cusk eels and their relatives (Ophidiiformes: Ophidioidei).

With 289 known species in 51 genera, the ophidiiform family Ophidiidae together with their relatives from the Carapidae (36 species in eight genera) of the same suborder Ophidioidei dominate the deep sea, but some occur also in shallow water habitats. Despite their high species diversity in the deep sea and wide bathymetric distributions, their phylogenetic relationships and evolution remain unexplored due in part to sampling difficulties. Thanks to the biodiversity exploratory program entitled "Tropical Deep-Sea Benthos" and joint efforts between Taiwan and French teams for sampling from different localities across the Indo-West Pacific over the last two decades, we are able to compile comprehensive datasets for investigations. In this study, 59 samples representing 36 of 59 known ophidioid genera are selected and used to construct a multi-gene dataset to infer the phylogenetic relationships of ophidioid fishes and their relatives. Our results reveal that the Ophidiidae forms a paraphyletic group with respect to the Carapidae. The four main clades of Ophidioidei resolved are the (1) clade comprising species from the subfamily Brotulinae; (2) clade that includes species in the genera Acanthonus and Xyelacyba; (3) clade grouping Hypopleuron caninum with species from the family Carapidae; and (4) clade containing the species in the subfamily Brotulotaenilinae, Neobythitinae (in part), and Ophidiinae. Accordingly, we suggest the following new revisions based on our results and proposed morphological diagnoses. The subfamily Brotulinae should be elevated to the family level. The genera Xyelacyba and probably Tauredophidium (unsampled in this study) should be included in the newly established family Acanthonidae with Acanthonus. The families Carapidae and Ophidiidae are re-defined. Our time-calibrated phylogenetic and ancestral depth reconstructions enable us to clarify the evolutionary history of ophidiiform fishes and infer past patterns of species distributions at different depths. While Ophidiiformes is inferred to have originated in shallow waters around 96.25 million years ago (Mya), the common ancestor to the Ophidioidei is inferred to have invaded the deep sea around 90.22 Mya, the dates coinciding with the global anoxic event of the OAE2. The observed bathymetric distribution patterns in Ophidioidei most likely point to the mesopelagic zone as the center of origin and diversification. This was followed by multiple events of depth transitions or range expansions towards either shallower waters or greater depth zones, which were likely triggered by past climate changes during the Paleogene-Neogene.

The application of machine learning methods for predicting the progression of adolescent idiopathic scoliosis: a systematic review.

Predicting curve progression during the initial visit is pivotal in the disease management of patients with adolescent idiopathic scoliosis (AIS)-identifying patients at high risk of progression is essential for timely and proactive interventions. Both radiological and clinical factors have been investigated as predictors of curve progression. With the evolution of machine learning technologies, the integration of multidimensional information now enables precise predictions of curve progression. This review focuses on the application of machine learning methods to predict AIS curve progression, analyzing 15 selected studies that utilize various machine learning models and the risk factors employed for predictions. Key findings indicate that machine learning models can provide higher precision in predictions compared to traditional methods, and their implementation could lead to more personalized patient management. However, due to the model interpretability and data complexity, more comprehensive and multi-center studies are needed to transition from research to clinical practice.

Raynaud's phenomenon on initiation of Lithium therapy: a case report.

Lithium Carbonate is an effective treatment for affective disorders, but has a range of side effects. This case report highlights a rare side effect of Raynaud's phenomenon following initiation of Lithium therapy in a patient with recurrent depressive disorder. He was commenced on Lithium therapy to treat severe treatment resistant depression with psychotic symptoms when alternative treatments trialled were ineffective. He had no other risk factors or known aetiological causes for development of Raynaud's phenomenon. Symptoms resolved on discontinuation of Lithium and re-emerged on recommencement. Previous case series have shown Lithium effectively treating vasospastic disorders such as cluster headache and Raynaud's phenomenon. However, a paradoxical reaction to those previously described was induced in this case.

Lignans from Sambucus williamsii Protect Bone Via Microbiome.

PURPOSE OF REVIEW: Traditional Chinese Medicine has a unique system to diagnose and treat bone diseases with symptoms similar to those of osteoporosis. Sambucus williamsii Hance (SWH), a folk medicine in northern part of China for fractures healing and pain alleviation, has been demonstrated to exert bone anabolic effects in ovariectomized (OVX) rat and mice models in our previous studies. Lignans were identified to be the main bioactive fractions of SWH. However, pharmacokinetics study showed that the levels of lignan were too low to be detected in rat serum even upon taking 15 times of the effective dose of lignan-rich fraction from SWH. We hypothesize that lignans from SWH might exert its bone protective effect via the gut microbiome. RECENT FINDINGS: Our study revealed that the lignan-rich fraction of SWH did not influence the diversity of gut microbiota in OVX rats, but significantly increased the abundance of a few phyla, in particular, the restoration of the abundance of several genera that was directly correlated with bone mineral density (BMD). In addition, a subsequent metabolomic study indicated that serotonin, a neurotransmitter synthesized in the intestine and influenced by gut microbiota, may be involved in mediating the bone protective action of the lignans. Gut-derived serotonin is thought to inhibit bone growth. Based on this finding, several inhibitors that suppressed the synthesis of serotonin were identified from the lignans of SWH. Our studies suggested that microbiome is an indispensable factor for lignans derived from S. willimasii to exert bone beneficial effects.

Smart probes for optical imaging of T cells and screening of anti-cancer immunotherapies.

T cells are an essential part of the immune system with crucial roles in adaptive response and the maintenance of tissue homeostasis. Depending on their microenvironment, T cells can be differentiated into multiple states with distinct functions. This myriad of cellular activities have prompted the development of numerous smart probes, ranging from small molecule fluorophores to nanoconstructs with variable molecular architectures and fluorescence emission mechanisms. In this Tutorial Review, we summarize recent efforts in the design, synthesis and application of smart probes for imaging T cells in tumors and inflammation sites by targeting metabolic and enzymatic biomarkers as well as specific surface receptors. Finally, we briefly review current strategies for how smart probes are employed to monitor the response of T cells to anti-cancer immunotherapies. We hope that this Review may help chemists, biologists and immunologists to design the next generation of molecular imaging probes for T cells and anti-cancer immunotherapies.

Integrating both restoration and regeneration potentials into real-world forest restoration planning: A case study of Hong Kong.

Forest restoration is a vital nature-based solution for mitigating climate change and land degradation. To ensure restoration effectiveness, the costs and benefits of alternative restoration strategies (i.e., active restoration vs. natural regeneration) need to be evaluated. Existing studies generally focus on maximum restoration potential, neglecting the recovery potential achievable through natural regeneration processes, leading to incomplete understanding of the true benefits and doubts about the necessity of active restoration. In this study, we introduce a multi-stage framework incorporating both restoration and regeneration potential into prioritized planning for ecosystem restoration. We used the vegetated landscape of Hong Kong (covering 728 km2) as our study system due to its comprehensive fine-resolution data and unique history of vegetation recovery, making it an ideal candidate to demonstrate the importance of this concept and inspire further research. We analyzed vegetation recovery status (i.e., recovering, degrading, and stable) over the past decade based on the canopy height data derived from multi-temporal airborne LiDAR. We assessed natural regeneration potential and maximum restoration potential separately, producing spatially-explicit predictions. Our results show that 44.9% of Hong Kong's vegetated area has showed evidence of recovery, but remaining gains through natural regeneration are limited, constituting around 4% of what could be attained through active restoration. We further estimated restoration priority by maximizing the restoration gain. When prioritizing 5% of degraded areas, the increment in canopy height could be up to 10.9%. Collectively, our findings highlight the importance of integrating both restoration and regeneration potential into restoration planning. The proposed framework can aid policymakers and land managers in optimizing forest restoration options and promoting the protection and recovery of fragile ecosystems.

meGPS: a multi-omics signature for hepatocellular carcinoma detection integrating methylome and transcriptome data.

MOTIVATION: Hepatocellular carcinoma (HCC) is a primary malignancy with a poor prognosis. Recently, multi-omics molecular-level measurement enables HCC diagnosis and prognosis prediction, which is crucial for early intervention of personalized therapy to diminish mortality. Here, we introduce a novel strategy utilizing DNA methylation and RNA expression data to achieve a multi-omics gene pair signature (GPS) for HCC discrimination. RESULTS: The immune genes with negative correlations between expression and promoter methylation are enriched in the highly connected cancer-related pathway network, which are considered as the candidates for HCC detection. After that, we separately construct a methylation GPS (mGPS) and an expression GPS (eGPS), and then assemble them as a meGPS with five gene pairs, in which the significant methylation and expression changes occur between HCC tumor and non-tumor groups. Reliable performance has been validated by independent tissue (age, gender and etiology) and blood datasets. This study proposes a procedure for multi-omics GPS identification and develops a novel HCC signature using both methylome and transcriptome data, suggesting potential molecular targets for the detection and therapy of HCC. AVAILABILITY AND IMPLEMENTATION: Models are available at https://github.com/bioinformaticStudy/meGPS.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

COVID-19 Mortality and Progress Toward Vaccinating Older Adults - World Health Organization, Worldwide, 2020-2022.

After the emergence of SARS-CoV-2 in late 2019, transmission expanded globally, and on January 30, 2020, COVID-19 was declared a public health emergency of international concern.* Analysis of the early Wuhan, China outbreak (1), subsequently confirmed by multiple other studies (2,3), found that 80% of deaths occurred among persons aged ≥60 years. In anticipation of the time needed for the global vaccine supply to meet all needs, the World Health Organization (WHO) published the Strategic Advisory Group of Experts on Immunization (SAGE) Values Framework and a roadmap for prioritizing use of COVID-19 vaccines in late 2020 (4,5), followed by a strategy brief to outline urgent actions in October 2021.† WHO described the general principles, objectives, and priorities needed to support country planning of vaccine rollout to minimize severe disease and death. A July 2022 update to the strategy brief§ prioritized vaccination of populations at increased risk, including older adults,¶ with the goal of 100% coverage with a complete COVID-19 vaccination series** for at-risk populations. Using available public data on COVID-19 mortality (reported deaths and model estimates) for 2020 and 2021 and the most recent reported COVID-19 vaccination coverage data from WHO, investigators performed descriptive analyses to examine age-specific mortality and global vaccination rollout among older adults (as defined by each country), stratified by country World Bank income status. Data quality and COVID-19 death reporting frequency varied by data source; however, persons aged ≥60 years accounted for >80% of the overall COVID-19 mortality across all income groups, with upper- and lower-middle-income countries accounting for 80% of the overall estimated excess mortality. Effective COVID-19 vaccines were authorized for use in December 2020, with global supply scaled up sufficiently to meet country needs by late 2021 (6). COVID-19 vaccines are safe and highly effective in reducing severe COVID-19, hospitalizations, and mortality (7,8); nevertheless, country-reported median completed primary series coverage among adults aged ≥60 years only reached 76% by the end of 2022, substantially below the WHO goal, especially in middle- and low-income countries. Increased efforts are needed to increase primary series and booster dose coverage among all older adults as recommended by WHO and national health authorities.

Whole blood transcriptomics identifies subclasses of pediatric septic shock.

BACKGROUND: Sepsis is a highly heterogeneous syndrome, which has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles. METHODS: The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses. RESULTS: Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells and less diverse T cell receptor repertoires. CONCLUSIONS: Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences. Trial Registration This is a secondary analysis of data generated as part of the observational CAF-PINT ancillary of the HALF-PINT study (NCT01565941). Registered March 29, 2012.

Icariin, a phytoestrogen, exerts rapid estrogenic actions through crosstalk of estrogen receptors in osteoblasts.

Icariin, a flavonoid glycoside derived from Epimedium brevicornum Maxim, exerts bone protective effects via estrogen receptors (ERs). This study aimed to investigate the role of ER-α66, ER-α36, and GPER in bone metabolism in osteoblasts following treatment with icariin. Human osteoblastic MG-63 cells and osteoblast-specific ER-α66 knockout mice were employed. The ERs crosstalk in the estrogenic action of icariin was evaluated in ER-α66-negative human embryonic kidney HEK293 cells. Icariin, like E2, regulated ER-α36 and GPER protein expression in osteoblasts by downregulating them and upregulating ER-α66. ER-α36 and GPER suppressed the actions of icariin and E2 in bone metabolism. However, the in vivo administration of E2 (2 mg/kg/day) or icariin (300 mg/kg/day) restored bone conditions in KO osteoblasts. ER-α36 and GPER expression increased significantly and rapidly activated and translocated in KO osteoblasts after treatment with E2 or icariin. ER-α36 overexpression in KO osteoblasts further promoted the OPG/RANKL ratio induced by E2 or icariin treatment. This study showed icariin and E2 elicit rapid estrogenic responses in bone through recruiting ER-α66, ER-α36, and GPER. Notably, in osteoblasts lacking ER-α66, ER-α36, and GPER mediate the estrogenic effects of icariin and E2, while in intact osteoblasts, ER-α36 and GPER act as negative regulators of ER-α66.

Development and Recent Advances in Lysine and N-Terminal Bioconjugation for Peptides and Proteins.

The demand for creation of protein diversity and regulation of protein function through native protein modification and post-translational modification has ignited the development of selective chemical modification methods for peptides and proteins. Chemical bioconjugation offers selective functionalization providing bioconjugates with desired properties and functions for diverse applications in chemical biology, medicine, and biomaterials. The amino group existing at the lysine residue and N-terminus of peptides and proteins has been extensively studied in bioconjugation because of its good nucleophilicity and high surface exposure. Herein, we review the development of chemical methods for modification of the amino groups on lysine residue and N-terminus featuring excellent selectivity, mild reaction conditions, short reaction time, high conversion, biocompatibility, and preservation of protein integrity. This review is organized based on the chemoselectivity and site-selectivity of the chemical bioconjugation reagents to the amino acid residues aiming to provide guidance for the selection of appropriate bioconjugation methods.

Identification of the Microbial Transformation Products of Secoisolariciresinol Using an Untargeted Metabolomics Approach and Evaluation of the Osteogenic Activities of the Metabolites.

Secoisolariciresinol (SECO) is one of the major lignans occurring in various grains, seeds, fruits, and vegetables. The gut microbiota plays an important role in the biotransformation of dietary lignans into enterolignans, which might exhibit more potent bioactivities than the precursor lignans. This study aimed to identify, synthesize, and evaluate the microbial metabolites of SECO and to develop efficient lead compounds from the metabolites for the treatment of osteoporosis. SECO was fermented with human gut microbiota in anaerobic or micro-aerobic environments at different time points. Samples derived from microbial transformation were analyzed using an untargeted metabolomics approach for metabolite identification. Nine metabolites were identified and synthesized. Their effects on cell viability, osteoblastic differentiation, and gene expression were examined. The results showed that five of the microbial metabolites exerted potential osteogenic effects similar to those of SECO or better. The results suggested that the enterolignans might account for the osteoporotic effects of SECO in vivo. Thus, the presence of the gut microbiota could offer a good way to form diverse enterolignans with bone-protective effects. The current study improves our understanding of the microbial transformation products of SECO and provides new approaches for new candidate identification in the treatment of osteoporosis.

Mucosal brushings for nasal specific IgE to predict house dust mite driven allergic rhinitis.

BACKGROUND: Skin prick testing and serological identification of allergen specific immunoglobulin E (spIgE) are standard tests for allergic rhinitis but can only identify systemic responses. In contrast, nasal allergen challenge (NAC), directly assess localized nasal mucosal reactivity, but is time consuming. Identification of spIgE from nasal brushings (nasal spIgE) is an alternative technique. OBJECTIVE: This study aimed to determine the diagnostic performance of nasal spIgE compared to NAC in order predict house dust mite (HDM) driven AR. METHODS: A diagnostic cross-sectional study involving adult rhinitis patients was performed. Sensitization to HDM allergens (Dermatophagoides pteronyssinus (DP), Dermatophagoides farina (DF) were assessed serologically and/or skin prick test, nasal brushing and NAC. Patients with both positive systemic test and NAC were defined to have HDM driven AR, while patients with a positive systemic test and negative NAC were defined to have non-clinically relevant HDM sensitization. The performance of nasal spIgE to predict positive NAC was determined using the receiver operating curve. The chosen cut-off was then used to predict HDM driven AR among those with positive systemic test. RESULTS: 118 patients (29.42 ± 9.32 years, 61.9% female) were included. Nasal spIgE was predictive of positive NAC (AUC 0.93, 95%CI: 0.88-0.98, p < 0.01). Among those with positive systemic test, the cut-off value of >0.14 kUA/L was able to predict HDM AR from incidental HDM sensitization with 92% sensitivity and 86% specificity. CONCLUSIONS: Nasal spIgE is comparable to NAC. A cut-off value of >0.14 kUA/L identifies HDM-driven AR from incidental sensitization among patients with positive systemic tests for allergy.