Network-based approach for drug repurposing against mpox.

The current outbreak of mpox presents a significant threat to the global community. However, the lack of mpox-specific drugs necessitates the identification of additional candidates for clinical trials. In this study, a network medicine framework was used to investigate poxviruses-human interactions to identify potential drugs effective against the mpox virus (MPXV). The results indicated that poxviruses preferentially target hubs on the human interactome, and that these virally-targeted proteins (VTPs) tend to aggregate together within specific modules. Comorbidity analysis revealed that mpox is closely related to immune system diseases. Based on predicted drug-target interactions, 268 drugs were identified using the network proximity approach, among which 23 drugs displaying the least side-effects and significant proximity to MPXV were selected as the final candidates. Lastly, specific drugs were explored based on VTPs, differentially expressed proteins, and intermediate nodes, corresponding to different categories. These findings provide novel insights that can contribute to a deeper understanding of the pathogenesis of MPXV and development of ready-to-use treatment strategies based on drug repurposing.

SAFER: sub-hypergraph attention-based neural network for predicting effective responses to dose combinations.

Background: The potential benefits of drug combination synergy in cancer medicine are significant, yet the risks must be carefully managed due to the possibility of increased toxicity. Although artificial intelligence applications have demonstrated notable success in predicting drug combination synergy, several key challenges persist: (1) Existing models often predict average synergy values across a restricted range of testing dosages, neglecting crucial dose amounts and the mechanisms of action of the drugs involved. (2) Many graph-based models rely on static protein-protein interactions, failing to adapt to dynamic and context-dependent networks. This limitation constrains the applicability of current methods. Results: We introduced SAFER, a Sub-hypergraph Attention-based graph model, addressing these issues by incorporating complex relationships among biological knowledge networks and considering dosing effects on subject-specific networks. SAFER outperformed previous models on the benchmark and the independent test set. The analysis of subgraph attention weight for the lung cancer cell line highlighted JAK-STAT signaling pathway, PRDM12, ZNF781, and CDC5L that have been implicated in lung fibrosis. Conclusions: SAFER presents an interpretable framework designed to identify drug-responsive signals. Tailored for comprehending dose effects on subject-specific molecular contexts, our model uniquely captures dose-level drug combination responses. This capability unlocks previously inaccessible avenues of investigation compared to earlier models. Finally, the SAFER framework can be leveraged by future inquiries to investigate molecular networks that uniquely characterize individual patients.

The efficiency and safety of temozolomide and PD-1/L1 inhibitors in pretreated NSCLC with brain metastasis: a retrospective cohort.

OBJECTIVE: Previous research has shown that both temozolomide (TMZ) and PD-1/L1 inhibitors (PD-1/L1) alone exhibit certain potential in the treatment of non-small cell lung cancer (NSCLC) with brain metastases (BM), in this study, we will explore combining the two in order to seek new effective treatment options for NSCLC with BM. MATERIAL AND METHODS: During 2021.1 to 2023.12, we collected the date of these pretreated-NSCLC with BM who accept the treatment of TMZ and PD-1/L1, the objective response ratio (ORR), progression-free survival (PFS) and overall survival (OS) were set as the primary endpoint, meanwhile, the toxicity of such regimen was also recorded. RESULTS: About 42 patients are enrolled, our primary analysis demonstrated that the ORR of such regimen toward NSCLC with BM was 26.19%, with Approximate intracranial and extracranial lesion ORR was 6% and 20% respectively, the DCR was about 64.29%, the mean PFS and OS was about 4 m and 8.5 m. Further analysis indicated that the efficiency correlated with the diagnosis-Specific Graded Prognostic Assessment (ds-GPA) score. Moreover, the toxicity can also be tolerated, indicating the application potential of such regimen against NSCLC with BM. CONCLUSIONS: Our results exhibited that with tolerated toxicity, the combination of TMZ and PD-1/L1 shows promising efficiency against NSCLC with BM, this would be of great significance for the treatment of NSCLC with brain metastasis. However, due to the limitation of sample and retrospective property, the real value of such regimen needed to be further confirmed in the future.

An integrated smartphone-based electrochemical detection system for highly sensitive and on-site detection of chemical oxygen demand by copper-cobalt bimetallic oxide-modified electrode.

A portable and integrated electrochemical detection system has been constructed for on-site and real-time detection of chemical oxygen demand (COD). The system mainly consists of four parts: (i) sensing electrode with a copper-cobalt bimetallic oxide (CuCoOx)-modified screen-printed electrode; (ii) an integrated electrochemical detector for the conversion, amplification, and transmission of weak signals; (iii) a smartphone installed with a self-developed Android application (APP) for issuing commands, receiving, and displaying detection results; and (iv) a 3D-printed microfluidic cell for the continuous input of water samples. Benefiting from the superior catalytic capability of CuCoOx, the developed system shows a high detection sensitivity with 0.335 µA/(mg/L) and a low detection limit of 5.957 mg/L for COD determination and possessing high anti-interference ability to chloride ions. Moreover, this system presents good consistency with the traditional dichromate method in COD detection of actual water samples. Due to the advantages of cost effectiveness, portability, and point-of-care testing, the system shows great potential for water quality monitoring, especially in resource-limited remote areas.

Genomic Surveillance for SARS-CoV-2 Variants: Dominance of XBB Replacement - China, January-June 2023.

Introduction: In the first half of 2023, a global shift was observed towards the predominance of XBB variants. China faced a significant epidemic between late 2022 and early 2023 due to Omicron subvariants BA.5.2 and BF.7. This study aims to depict the evolving variant distribution among provincial-level administrative divisions (PLADs) in China and explore the factors driving the predominance of XBB replacement. Methods: Sequences from local and imported coronavirus disease 2019 (COVID-19) cases recorded between January 1 and June 30, 2023, were included. The study analyzed the changing distribution of viral variants and assessed how the prior dominance of specific variants, XBB subvariants, and imported cases influenced the prevalence of the XBB replacement variant. Results: A total of 56,486 sequences were obtained from local cases, and 8,669 sequences were from imported cases. Starting in April, there was a shift in the prevalence of XBB from imported to local cases, with varying dominance among PLADs. In PLADs previously high in BF.7, the rise of XBB was delayed. A positive correlation was found between XBB proportions in imported cases from January to March and local cases in April. The distribution pattern of XBB subvariants differed between local and imported cases within the same PLAD. No significant differences were noted in the replacement rates of XBB subvariants. Conclusions: The timing of XBB dominance differed among various PLADs in China in the first half of 2023, correlating closely with the prevalence of XBB variants among imported cases.

Spinal projecting neurons in rostral ventromedial medulla co-regulate motor and sympathetic tone.

Many behaviors require the coordinated actions of somatic and autonomic functions. However, the underlying mechanisms remain elusive. By opto-stimulating different populations of descending spinal projecting neurons (SPNs) in anesthetized mice, we show that stimulation of excitatory SPNs in the rostral ventromedial medulla (rVMM) resulted in a simultaneous increase in somatomotor and sympathetic activities. Conversely, opto-stimulation of rVMM inhibitory SPNs decreased both activities. Anatomically, these SPNs innervate both sympathetic preganglionic neurons and motor-related regions in the spinal cord. Fiber-photometry recording indicated that the activities of rVMM SPNs correlate with different levels of muscle and sympathetic tone during distinct arousal states. Inhibiting rVMM excitatory SPNs reduced basal muscle and sympathetic tone, impairing locomotion initiation and high-speed performance. In contrast, silencing the inhibitory population abolished muscle atonia and sympathetic hypoactivity during rapid eye movement (REM) sleep. Together, these results identify rVMM SPNs as descending spinal projecting pathways controlling the tone of both the somatomotor and sympathetic systems.

A critical assessment of Traditional Chinese Medicine databases as a source for drug discovery.

Traditional Chinese Medicine (TCM) has been used for thousands of years to treat human diseases. Recently, many databases have been devoted to studying TCM pharmacology. Most of these databases include information about the active ingredients of TCM herbs and their disease indications. These databases enable researchers to interrogate the mechanisms of action of TCM systematically. However, there is a need for comparative studies of these databases, as they are derived from various resources with different data processing methods. In this review, we provide a comprehensive analysis of the existing TCM databases. We found that the information complements each other by comparing herbs, ingredients, and herb-ingredient pairs in these databases. Therefore, data harmonization is vital to use all the available information fully. Moreover, different TCM databases may contain various annotation types for herbs or ingredients, notably for the chemical structure of ingredients, making it challenging to integrate data from them. We also highlight the latest TCM databases on symptoms or gene expressions, suggesting that using multi-omics data and advanced bioinformatics approaches may provide new insights for drug discovery in TCM. In summary, such a comparative study would help improve the understanding of data complexity that may ultimately motivate more efficient and more standardized strategies towards the digitalization of TCM.

Global pattern and determinant for interaction of seasonal influenza viruses.

BACKGROUND: The prevalence of different types/subtypes varies across seasons and countries for seasonal influenza viruses, indicating underlying interactions between types/subtypes. The global interaction patterns and determinants for seasonal influenza types/subtypes need to be explored. METHODS: Influenza epidemiological surveillance data, as well as multidimensional data that include population-related, environment-related, and virus-related factors from 55 countries worldwide were used to explore type/subtype interactions based on Spearman correlation coefficient. The machine learning method Extreme Gradient Boosting (XGBoost) and interpretable framework SHapley Additive exPlanation (SHAP) were utilized to quantify contributing factors and their effects on interactions among influenza types/subtypes. Additionally, causal relationships between types/subtypes were also explored based on Convergent Cross-mapping (CCM). RESULTS: A consistent globally negative correlation exists between influenza A/H3N2 and A/H1N1. Meanwhile, interactions between influenza A (A/H3N2, A/H1N1) and B show significant differences across countries, primarily influenced by population-related factors. Influenza A has a stronger driving force than influenza B, and A/H3N2 has a stronger driving force than A/H1N1. CONCLUSION: The research elucidated the globally complex and heterogeneous interaction patterns among influenza type/subtypes, identifying key factors shaping their interactions. This sheds light on better seasonal influenza prediction and model construction, informing targeted prevention strategies and ultimately reducing the global burden of seasonal influenza.

Detoxification and underlying mechanisms towards toxic alkaloids by Traditional Chinese Medicine processing: A comprehensive review.

BACKGROUND: Alkaloids have attracted enduring interest worldwide due to their remarkable therapeutic effects, including analgesic, anti-inflammatory, and anti-tumor properties, thus offering a rich source for lead compound design and new drug discovery. However, some of these alkaloids possess intrinsic toxicity. Processing (Paozhi) is a pre-treatment step before the application of herbal medicines in traditional Chinese medicine (TCM) clinics, which has been employed for centuries to mitigate the toxicity of alkaloid-rich TCMs. PURPOSE: To explore the toxicity phenotypes, chemical basis, mode of action, detoxification processing methods, and underlying mechanisms, we can gain crucial insights into the safe and rational use of these toxic alkaloid-rich herbs. Such insights have the great potential to offer new strategies for drug discovery and development, ultimately improving the quality of life for millions of people. METHODS: Literatures published or early accessed until December 31, 2023, were retrieved from databases including PubMed, Web of Science, and CNKI. The following keywords, such as "toxicity", "alkaloid", "detoxification", "processing", "traditional Chinese medicine", "medicinal plant", and "plant", were used in combination or separately for screening. RESULTS: Toxicity of alkaloids in TCM includes hepatotoxicity, nephrotoxicity, neurotoxicity, cardiotoxicity, and other forms of toxicity, primarily induced by pyrrolizidines, quinolizidines, isoquinolines, indoles, pyridines, terpenoids, and amines. Factors such as whether the toxic-alkaloid enriched part is limited or heat-sensitive, and whether toxic alkaloids are also therapeutic components, are critical for choosing appropriate detoxification processing methods. Mechanisms of alkaloid detoxification includes physical removal, chemical decomposition or transformation, as well as biological modifications. CONCLUSION: Through this exploration, we review toxic alkaloids and the mechanisms underlying their toxicity, discuss methods to reduce toxicity, and unravel the intricate mechanisms behind detoxification. These offers insights into the quality control of herbs containing toxic alkaloids, safe and rational use of alkaloid-rich TCMs in clinics, new strategies for drug discovery and development, and ultimately helping improve the quality of life for millions of people.

Opening the black box: spatial transcriptomics and the relevance of AI-detected prognostic regions in high grade serous carcinoma.

Image based deep learning models are used to extract new information from standard H&E pathology slides, however, biological interpretation of the features detected by artificial intelligence (AI) remains a challenge. High-grade serous ovarian carcinoma (HGSC) is characterized by aggressive behavior and chemotherapy resistance, but also by striking variability in outcome. Our understanding of this disease is limited, partly due to considerable tumor heterogeneity. We previously trained an AI model to identify HGSC tumor regions that are highly associated with outcome status but are indistinguishable by conventional morphologic methods. Here we applied spatial transcriptomics to further profile the AI-identified tumor regions in 16 patients (8 per outcome group) and identify molecular features related to disease outcome in patients who underwent primary debulking surgery and platinum-based chemotherapy. We examined FFPE tissue from 1) regions identified by the AI model as highly associated with short or extended chemotherapy response, and 2) background tumor regions (not identified by the AI model as highly associated with outcome status) from the same tumors. We show that the transcriptomic profiles of AI-identified regions are more distinct than background regions from the same tumors, are superior in predicting outcome, and differ in several pathways including those associated with chemoresistance in HGSC. Further, we find that poor outcome and good outcome regions are enriched by different tumor subpopulations, suggesting distinctive interaction patterns. In summary, our work presents proof of concept that AI-guided spatial transcriptomic analysis improves recognition of biologic features relevant to patient outcome.

Stromal lenticule addition keratoplasty with corneal crosslinking for corneal ectasia secondary to FS-LASIK: a case series.

AIM: To explore the clinical efficacy and safety of stromal lenticule addition keratoplasty (SLAK) with corneal crosslinking (CXL) on patients with corneal ectasia secondary to femtosecond laser-assisted in situ keratomileusis (FS-LASIK). METHODS: A series of 5 patients undertaking SLAK with CXL for the treatment of corneal ectasia secondary to FS-LASIK were followed for 4-9mo. The lenticules were collected from patients undertaking small incision lenticule extraction (SMILE) for the correction of myopia. Adding a stromal lenticule was aimed at improving the corneal thickness for the safe application of crosslinking and compensating for the thin cornea to improve its mechanical strength. RESULTS: All surgeries were conducted successfully with no significant complications. Their best corrected visual acuity (BCVA) ranged from 0.05 to 0.8-2 before surgery. The pre-operational total corneal thickness ranged from 345-404 µm and maximum keratometry (Kmax) ranged from 50.8 to 86.3. After the combination surgery, both the corneal keratometry (range 55.9 to 92.8) and total corneal thickness (range 413-482 µm) significantly increased. Four out of 5 patients had improvement of corneal biomechanical parameters (reflected by stiffness parameter A1 in Corvis ST). However, 3 patients showed decreased BCVA after surgery due to the development of irregular astigmatism and transient haze. Despite the onset of corneal edema right after SLAK, the corneal topography and thickness generally stabilized after 3mo. CONCLUSION: SLAK with CXL is a potentially beneficial and safe therapy for advanced corneal ectasia. Future work needs to address the poor predictability of corneal refractometry and compare the outcomes of different surgical modes.

Palmitic acid impairs human and mouse placental function by inhibiting trophoblast autophagy through induction of acyl-coenzyme A-binding protein (ACBP) upregulation.

STUDY QUESTION: Can exposure to palmitic acid (PA), a common saturated fatty acid, modulate autophagy in both human and mouse trophoblast cells through the regulation of acyl-coenzyme A-binding protein (ACBP)? SUMMARY ANSWER: PA exposure before and during pregnancy impairs placental development through mechanisms involving placental autophagy and ACBP expression. WHAT IS KNOWN ALREADY: High-fat diets, including PA, have been implicated in adverse effects on human placental and fetal development. Despite this recognition, the precise molecular mechanisms underlying these effects are not fully understood. STUDY DESIGN, SIZE, DURATION: Extravillous trophoblast (EVT) cell line HTR-8/SVneo and human trophoblast stem cell (hTSC)-derived EVT (hTSCs-EVT) were exposed to PA or vehicle control for 24 h. Female wild-type C57BL/6 mice were divided into PA and control groups (n = 10 per group) and subjected to a 12-week dietary intervention. Afterward, they were mated with male wild-type C57BL/6 mice and euthanized on Day 14 of gestation. Female ACBPflox/flox mice were also randomly assigned to control and PA-exposed groups (each with 10 mice), undergoing the same dietary intervention and mating with ACBPflox/floxELF5-Cre male mice, followed by euthanasia on Day 14 of gestation. The study assessed the effects of PA on mouse embryonic development and placental autophagy. Additionally, the role of ACBP in the pathogenesis of PA-induced placental toxicity was investigated. PARTICIPANTS/MATERIALS, SETTING, METHODS: The findings were validated using real-time PCR, Western blot, immunofluorescence, transmission electron microscopy, and shRNA knockdown approaches. MAIN RESULTS AND THE ROLE OF CHANCE: Exposure to PA-upregulated ACBP expression in both human HTR-8/SVneo cells and hTSCs-EVT, as well as in mouse placenta. PA exposure also induced autophagic dysfunction in HTR-8/SVneo cells, hTSCs-EVT, and mouse placenta. Through studies on ACBP placental conditional knockout mice and ACBP knockdown human trophoblast cells, it was revealed that reduced ACBP expression led to trophoblast malfunction and affected the expression of autophagy-related proteins LC3B-II and P62, thereby impacting embryonic development. Conversely, ACBP knockdown partially mitigated PA-induced impairment of placental trophoblast autophagy, observed both in vitro in human trophoblast cells and in vivo in mice. LARGE SCALE DATA: N/A. LIMITATIONS, REASONS FOR CAUTION: Primary EVT cells from early pregnancy are fragile, limiting research use. Maintaining their viability is tough, affecting data reliability. The study lacks depth to explore PA diet cessation effects after 12 weeks. Without follow-up, understanding postdiet impacts on pregnancy stages is incomplete. Placental abnormalities linked to elevated PA diet in embryos lack confirmation due to absence of control groups. Clarifying if issues stem solely from PA exposure is difficult without proper controls. WIDER IMPLICATIONS OF THE FINDINGS: Consuming a high-fat diet before and during pregnancy may result in complications or challenges in successfully carrying the pregnancy to term. It suggests that such dietary habits can have detrimental effects on the health of both the mother and the developing fetus. STUDY FUNDING/COMPETING INTEREST(S): This work was supported in part by the National Natural Science Foundation of China (82171664, 82301909) and the Natural Science Foundation of Chongqing Municipality of China (CSTB2022NS·CQ-LZX0062, cstc2019jcyj-msxmX0749, and cstc2021jcyj-msxmX0236). The authors declare that they have no conflict of interest. TRIAL REGISTRATION NUMBER: N/A.

Characterizing the antigenic evolution of pandemic influenza A (H1N1) pdm09 from 2009 to 2023.

The H1N1pdm09 virus has been a persistent threat to public health since the 2009 pandemic. Particularly, since the relaxation of COVID-19 pandemic mitigation measures, the influenza virus and SARS-CoV-2 have been concurrently prevalent worldwide. To determine the antigenic evolution pattern of H1N1pdm09 and develop preventive countermeasures, we collected influenza sequence data and immunological data to establish a new antigenic evolution analysis framework. A machine learning model (XGBoost, accuracy = 0.86, area under the receiver operating characteristic curve = 0.89) was constructed using epitopes, physicochemical properties, receptor binding sites, and glycosylation sites as features to predict the antigenic similarity relationships between influenza strains. An antigenic correlation network was constructed, and the Markov clustering algorithm was used to identify antigenic clusters. Subsequently, the antigenic evolution pattern of H1N1pdm09 was analyzed at the global and regional scales across three continents. We found that H1N1pdm09 evolved into around five antigenic clusters between 2009 and 2023 and that their antigenic evolution trajectories were characterized by cocirculation of multiple clusters, low-level persistence of former dominant clusters, and local heterogeneity of cluster circulations. Furthermore, compared with the seasonal H1N1 virus, the potential cluster-transition determining sites of H1N1pdm09 were restricted to epitopes Sa and Sb. This study demonstrated the effectiveness of machine learning methods for characterizing antigenic evolution of viruses, developed a specific model to rapidly identify H1N1pdm09 antigenic variants, and elucidated their evolutionary patterns. Our findings may provide valuable support for the implementation of effective surveillance strategies and targeted prevention efforts to mitigate the impact of H1N1pdm09.

Development of a novel fluorescent protein-based probe for efficient detection of Pb2+ in serum inspired by the metalloregulatory protein PbrR691.

BACKGROUND: The accurate and rapid detection of blood lead concentration is of paramount importance for assessing human lead exposure levels. Fluorescent protein-based probes, known for their high detection capabilities and low toxicity, are extensively used in analytical sciences. However, there is currently a shortage of such probes designed for ultrasensitive detection of Pb2+, and no reported probes exist for the quantitative detection of Pb2+ in blood samples. This study aims to fill this critical void by developing and evaluating a novel fluorescent protein-based probe that promises accurate and rapid lead quantification in blood. RESULTS: A simple and small-molecule fluorescent protein-based probe was successfully constructed herein using a peptide PbrBD designed for Pb2+ recognition coupled to a single fluorescent protein, sfGFP. The probe retains a three-coordinate configuration to identify Pb2+ and has a high affinity for it with a Kd' of 1.48 ± 0.05 × 10-17 M. It effectively transfers the conformational changes of the peptide to the chromophore upon Pb2+ binding, leading to fast fluorescence quenching and a sensitive response to Pb2+. The probe offers a broad dynamic response range of approximately 37-fold and a linear detection range from 0.25 nM to 3500 nM. More importantly, the probe can resist interference of metal ions in living organisms, enabling quantitative analysis of Pb2+ in the picomolar to millimolar range in serum samples with a recovery percentage of 96.64%-108.74 %. SIGNIFICANCE: This innovative probe, the first to employ a single fluorescent protein-based probe for ultrasensitive and precise analysis of Pb2+ in animal and human serum, heralds a significant advancement in environmental monitoring and public health surveillance. Furthermore, as a genetically encoded fluorescent probe, this probe also holds potential for the in vivo localization and concentration monitoring of Pb2+.

Carbon capture in polymer-based electrolytes.

Nanoparticle organic hybrid materials (NOHMs) have been proposed as excellent electrolytes for combined CO2 capture and electrochemical conversion due to their conductive nature and chemical tunability. However, CO2 capture behavior and transport properties of these electrolytes after CO2 capture have not yet been studied. Here, we use a variety of nuclear magnetic resonance (NMR) techniques to explore the carbon speciation and transport properties of branched polyethylenimine (PEI) and PEI-grafted silica nanoparticles (denoted as NOHM-I-PEI) after CO2 capture. Quantitative 13C NMR spectra collected at variable temperatures reveal that absorbed CO2 exists as carbamates (RHNCOO- or RR'NCOO-) and carbonate/bicarbonate (CO32-/HCO3-). The transport properties of PEI and NOHM-I-PEI studied using 1H pulsed-field-gradient NMR, combined with molecular dynamics simulations, demonstrate that coulombic interactions between negatively and positively charged chains dominate in PEI, while the self-diffusion in NOHM-I-PEI is dominated by silica nanoparticles. These results provide strategies for selecting adsorbed forms of carbon for electrochemical reduction.

The allostery and modification of hGHRH molecules and specific dimer produced significant fertility effect by proliferating and activating in-situ ovarian mesenchymal stem cells.

The negative coordination of growth hormone secretagogue receptor (GHS-R) and growth hormone-releasing hormone receptor (GHRH-R) involves in the repair processes of cellular injury. The allosteric U- or H-like modified GHRH dimer Grinodin and 2Y were comparatively evaluated in normal Kunming mice and hamster infertility models induced by CPA treatment. 1-3-9 µg of Grinodin or 2Y per hamster stem-cell-exhaustion model was subcutaneously administered once a week, respectively inducing 75-69-46 or 45-13-50 % of birth rates. In comparison, the similar mole of human menopausal gonadotropin (hMG) or human growth hormone (hGH) was administered once a day but caused just 25 or 20 % of birth rates. Grinodin induced more big ovarian follicles and corpora lutea than 2Y, hMG, hGH. The hMG-treated group was observed many distorted interstitial cells and more connective tissues and the hGH-treated group had few ovarian follicles. 2Y had a plasma lifetime of 21 days and higher GH release in mice, inducing lower birth rate and stronger individual specificity in reproduction as well as only promoting the proliferation of mesenchymal-stem-cells (MSCs) in the models. In comparison, Grinodin had a plasma lifetime of 30 days and much lower GH release in mice. It significantly promoted the proliferation and activation of ovarian MSCs together with the development of follicles in the models by increasing Ki67 and GHS-R expressions, and decreasing GHRH-R expression in a dose-dependent manner. However, the high GH and excessive estrogen levels in the models showed a dose-dependent reduction in fertility. Therefore, unlike 2Y, the low dose of Grinodin specifically shows low GHS-R and high GHRH-R expressions thus evades GH and estrogen release and improves functions of organs, resulting in an increase of fertility.

Exosomal Tenascin-C primes macrophage pyroptosis amplifying aberrant inflammation during sepsis-induced acute lung injury.

Sepsis-induced acute lung injury (ALI) is a serious complication of sepsis and the predominant cause of death. Exosomes released by lung tissue cells critically influence the progression of ALI during sepsis by modulating the inflammatory microenvironment. However, the molecular mechanisms by which exosome-mediated intercellular signaling exacerbates ALI in septic infection remain undefined. Our study found increased levels of exosomal Tenascin-C (TNC) in the plasma of both patients and mice with ALI, showing a strong association with disease progression. By integrating exosomal proteomics with transcriptome sequencing and experimental validation, we elucidated that LPS induce unresolved endoplasmic reticulum stress (ERs) in alveolar epithelial cells (AECs), ultimately leading to the release of exosomal TNC through the activation of PERK-eIF2α and the transcription factor CHOP. In the sepsis mouse model with TNC knockout, we noted a marked reduction in macrophage pyroptosis. Our detailed investigations found that exosomal TNC binds to TLR4 on macrophages, resulting in an augmented production of ROS, subsequent mitochondrial damage, activation of the NF-κB signaling pathway, and induction of DNA damage response. These interconnected events culminate in macrophage pyroptosis, thereby amplifying the release of inflammatory cytokines. Our findings demonstrate that exosomal Tenascin-C, released from AECs under unresolved ER stress, exacerbates acute lung injury by intensifying sepsis-associated inflammatory responses. This research provides new insights into the complex cellular interactions underlying sepsis-induced ALI.

From 2D to 3D: Automatic measurement of the Cobb angle in adolescent idiopathic scoliosis with the weight-bearing 3D imaging.

BACKGROUND CONTEXT: Adolescent idiopathic scoliosis (AIS) necessitates accurate spinal curvature assessment for effective clinical management. Traditional two-dimensional (2D) Cobb angle measurements have been the standard, but the emergence of three-dimensional (3D) automatic measurement techniques, such as those using weight-bearing 3D imaging (WR3D), presents an opportunity to enhance the accuracy and comprehensiveness of AIS evaluation. PURPOSE: This study aimed to compare traditional 2D Cobb angle measurements with 3D automatic measurements utilizing the WR3D imaging technique in patients with AIS. STUDY DESIGN/SETTING: A cohort of 53 AIS patients was recruited, encompassing 88 spinal curves, for comparative analysis. PATIENT SAMPLE: The patient sample consisted of 53 individuals diagnosed with AIS. OUTCOME MEASURES: Cobb angles were calculated using the conventional 2D method and three different 3D methods: the Analytical Method (AM), the Plane Intersecting Method (PIM), and the Plane Projection Method (PPM). METHODS: The 2D cobb angle was manually measured by 3 experienced clinicians with 2D frontal whole-spine radiographs. For 3D cobb angle measurements, the spine and femoral heads were segmented from the WR3D images using a 3D-UNet deep-learning model, and the automatic calculations of the angles were performed with the 3D slicer software. RESULTS: AM and PIM estimates were found to be significantly larger than 2D measurements. Conversely, PPM results showed no statistical difference compared to the 2D method. These findings were consistent in a subgroup analysis based on 2D Cobb angles. CONCLUSION: Each 3D measurement method provides a unique assessment of spinal curvature, with PPM offering values closely resembling 2D measurements, while AM and PIM yield larger estimations. The utilization of WR3D technology alongside deep learning segmentation ensures accuracy and efficiency in comparative analyses. However, additional studies, particularly involving patients with severe curves, are required to validate and expand on these results. This study emphasizes the importance of selecting an appropriate measurement method considering the imaging modality and clinical context when assessing AIS, and it also underlines the need for continuous refinement of these techniques for optimal use in clinical decision-making and patient management.