Eur J Cell Biol. 2025 Jan 15;104(2):151476. doi: 10.1016/j.ejcb.2025.151476. Online ahead of print.

ABSTRACT

Since the development of the three-dimensional (3D) "mini-gut" culture system, adult stem cell-derived organoid technology has rapidly advanced, providing in vitro models that replicate key cellular, molecular, and physiological properties of multiple organs. The 3D intestinal organoid system has resolved many long-standing challenges associated with immortalized or cancer cell cultures, offering unparalleled capabilities for modeling gastrointestinal development and diseases. However, significant limitations remain, including restricted accessibility to the epithelial apical surface for studying host-microbe interactions, interruptions in modeling chronic gastrointestinal diseases due to frequent passaging and dissociation, and the absence of mechanical cues such as peristalsis and luminal flow, which are critical for organ development and function. To address these challenges, recent advancements have introduced Transwell-based monolayer cultures and microfluidic device-based technologies including "organ-on-a-chip" and scaffold-guided 'mini-gut' system. This review highlights these innovations, with a focus on adult stem cell-derived intestinal organoid models that feature an open apical surface and discusses their prospects and challenges for advancing basic research and clinical applications.

PMID:39837176 | DOI:10.1016/j.ejcb.2025.151476

PLoS Biol. 2025 Jan 21;23(1):e3002982. doi: 10.1371/journal.pbio.3002982. Online ahead of print.

ABSTRACT

Coronaviruses express their structural and accessory genes via a set of subgenomic RNAs, whose synthesis is directed by transcription regulatory sequences (TRSs) in the 5' genomic leader and upstream of each body open reading frame. In SARS-CoV-2, the TRS has the consensus AAACGAAC; upon searching for emergence of this motif in the global SARS-CoV-2 sequences, we find that it evolves frequently, especially in the 3' end of the genome. We show well-supported examples upstream of the Spike gene-within the nsp16 coding region of ORF1b-which is expressed during human infection, and upstream of the canonical Envelope gene TRS, both of which have evolved convergently in multiple lineages. The most frequent neo-TRS is within the coding region of the Nucleocapsid gene, and is present in virtually all viruses from the B.1.1 lineage, including the variants of concern Alpha, Gamma, Omicron and descendants thereof. Here, we demonstrate that this TRS leads to the expression of a novel subgenomic mRNA encoding a truncated C-terminal portion of Nucleocapsid, which is an antagonist of type I interferon production and contributes to viral fitness during infection. We observe distinct phenotypes when the Nucleocapsid coding sequence is mutated compared to when the TRS alone is ablated. Our findings demonstrate that SARS-CoV-2 is undergoing evolutionary changes at the functional RNA level in addition to the amino acid level.

PMID:39836705 | DOI:10.1371/journal.pbio.3002982

Mini Rev Med Chem. 2025 Jan 17. doi: 10.2174/0113895575339660250106093738. Online ahead of print.

ABSTRACT

Metabolic reprogramming is a hallmark of cancer. Distinct and unusual metabolic aberrations occur during tumor development that lead to the growth and development of tumors. Oncogenic signaling pathways eventually converge to regulate three major metabolic pathways in tumor cells i.e., glucose, lipid, and amino acid metabolism. Therefore, identifying and targeting the metabolic nodes of cancer cells can be a promising intervention and therapeutic strategy for patients with malignancies. The long road of new drug discovery for cancer therapy has necessitated relooking alternative strategies such as drug repurposing. Advanced genomic and proteomic technologies for the assessment of cancer-specific biological pathways have led to the discovery of new drug targets, which provide excellent opportunities for drug repurposing. The development of effective, safe, cheaper, and readily available anticancer agents is the need of the hour, and drug repurposing has the potential to break the current drug shortage bottleneck. This review will accordingly cover various metabolic pathways that are aberrant in cancer, and strategies for targeting metabolic reprogramming by using repurposed drugs.

PMID:39835565 | DOI:10.2174/0113895575339660250106093738

Expert Opin Drug Metab Toxicol. 2025 Jan 21:1-28. doi: 10.1080/17425255.2024.2433626. Online ahead of print.

ABSTRACT

INTRODUCTION: Genetic load influences the therapeutic response to conventional drugs in Alzheimer's disease (AD). Pharmacogenetics (PGx) is the best option to reduce drug-drug interactions and adverse drug reactions in patients undergoing polypharmacy regimens. However, there are important limitations that make it difficult to incorporate pharmacogenetics into routine clinical practice.

AREAS COVERED: This article analyzes the pharmacogenetic apparatus made up of pathogenic, mechanistic, metabolic, transporter, and pleiotropic genes responsible for the efficacy and safety of pharmacological treatment, the impact of genetic load on the outcome of multifactorial treatments, and practical aspects for the effective use of PGx.

EXPERT OPINION: Over 120 genes are closely associated with AD. There is an accumulation of cerebrovascular (CVn) and neurodegenerative (ADn) genes in AD. APOE-4 carriers accumulate more deleterious genetic load related to other CVn and ADn genes, develop the disease earlier, and are at a biological disadvantage compared to APOE-4 non-carriers. CYP2D6-PMs and APOE-4 carriers are the worst responders to anti-dementia drugs. Some limitations hinder the implementation of PGx in clinical practice, including lack of pharmacogenetic information for many drugs, low number of genes in PGx screening protocols, and educational deficiencies in the medical community regarding PGx and genomic medicine.

PMID:39835706 | DOI:10.1080/17425255.2024.2433626

Am J Physiol Lung Cell Mol Physiol. 2025 Jan 21. doi: 10.1152/ajplung.00328.2024. Online ahead of print.

ABSTRACT

Background: Secondhand smoke exposure (SHSe) is a public health threat for people with cystic fibrosis (CF) and other lung diseases. Primary smoking reduces CFTR channel function, the causative defect in CF. We reported that SHSe worsens respiratory and nutritional outcomes in CF by disrupting immune responses and metabolic signaling. Recently, electronic cigarette (e-cigs) usage by caregivers and peers has increased rapidly, causing new secondhand e-cig vape exposures. Primary vaping is associated with immunologic deficits in healthy people, but it is unknown if e-cigs similarly impacts CF immune function or how it differs from SHSe. Methods: Human CF and non-CF blood monocyte derived macrophages (MDMs) and bronchial epithelial cells (HBECs) were exposed to flavored and unflavored e-cigs. The effect of e-cigs on CFTR expression and function, bacterial killing, cytokine signaling, lipid mediators, and metabolism was measured during treatment with CFTR modulators. Results: E-cigs decreased CFTR expression and function in CF and non-CF MDMs and negated CFTR functional restoration by elexacaftor/tezacaftor/ivacaftor (ETI). E-cigs also negated the restoration of anti-inflammatory PGD2 expression in CF MDMs treated with ETI compared to controls. Flavored but not unflavored e-cigs increased pro-inflammatory cytokine expression in CF MDMs and e-cigs promoted glycolytic metabolism. E-cigs did not impact bacterial killing. Overall, HBECs were less impacted by e-cigs compared to MDMs. Conclusion: E-cigs reduced macrophage CFTR expression and hindered functional CFTR restoration by CFTR modulators, promoting a glycolytic, pro-inflammatory state. E-cigs are an emerging public health threat that may limit the efficacy of CFTR modulators in people with CF.

PMID:39836014 | DOI:10.1152/ajplung.00328.2024

Pediatr Pulmonol. 2025 Jan;60(1):e27487. doi: 10.1002/ppul.27487.

ABSTRACT

OBJECTIVE: Although studies have examined changes in C-reactive protein (CRP) during pulmonary exacerbations (PEX) in people with cystic fibrosis (PwCF), few have evaluated CRP profiles across age groups. Here, we characterize age-related CRP responses to PEX treatment.

METHODS: We measured CRP concentrations at the beginning and end of intravenous (IV) antibiotic therapy for PEX in 100 pediatric and 147 adult PwCF at 10 US CF Centers. We examined relationships between CRP and age, lung function, severity of PEX symptoms, and time to next PEX.

RESULTS: CRP measured at initiation of IV antibiotic treatment for PEX was higher in adults than children, median 8 mg/L (IQR 4, 32) versus 5 mg/L (IQR 2, 10), respectively (p < 0.001). There was a significant correlation between the initial CRP and drop in lung from baseline to the beginning of IV antibiotics in adults and children. Adjusted CRP dropped in response to PEX treatment more commonly in adults than in children (70% vs. 48%, respectively). The range of treatment responses was greater in adults, in those with higher symptom scores, and in those with more advanced lung disease. In adults elevated CRP at the end of treatment was also associated with incomplete recovery of lung function. CRP at the start of IV antibiotics was inversely related to time until the next PEX.

CONCLUSION: In children and adults with CF, CRP is increased at the initiation of IV antibiotic therapy for PEX and declines with treatment. The response is more pronounced in highly symptomatic adults with advanced lung disease.

PMID:39835779 | DOI:10.1002/ppul.27487

Pediatr Pulmonol. 2025 Jan;60(1):e27488. doi: 10.1002/ppul.27488.

ABSTRACT

INTRODUCTION: Cellular characteristics of induced sputum (IS) are not investigated in cystic fibrosis (CF) patients.

OBJECTIVES: This pilot study, conducted on 17 expectorating CF adolescents, compared sputa obtained the same day, in a stable period, by autogenic drainage (expectorating sputum, ES) and 4 h later after inhaling hypertonic saline (IS).

RESULTS: No difference was noted concerning weight, volume, and percentage of dead cells between the two collection methods. Sample quality (< 50% of dead cells and < 20% squamous cells) was higher in the case of IS than ES (94.1% vs. 58.8%, p = 0.03), with a doubled cell count (p = 0.01), a higher proportion of alveolar macrophages (p = 0.03), and a lower proportion of squamous cells (p = 0.004). The detection of germs increased by 44% in IS samples, possibly modifying therapeutic management in 17.6% of the patients.

CONCLUSION: IS improves the quality and the microbiological detection of the sample, even among CF patients who spontaneously expectorate.

PMID:39835741 | DOI:10.1002/ppul.27488

Int J Comput Assist Radiol Surg. 2025 Jan 21. doi: 10.1007/s11548-025-03321-4. Online ahead of print.

ABSTRACT

PURPOSE: Identifying muscles linked to postoperative physical function can guide protocols to enhance early recovery following total hip arthroplasty (THA). This study aimed to evaluate the association of preoperative pelvic and thigh muscle volume and quality with early physical function after THA in patients with unilateral hip osteoarthritis (HOA).

METHODS: Preoperative Computed tomography (CT) images of 61 patients (eight males and 53 females) with HOA were analyzed. Six muscle groups were segmented from CT images, and muscle volume and quality were calculated on the healthy and affected sides. Muscle quality was quantified using the mean CT values (Hounsfield units [HU]). Early postoperative physical function was evaluated using the Timed Up & Go test (TUG) at three weeks after THA. The effect of preoperative muscle volume and quality of both sides on early postoperative physical function was assessed.

RESULTS: On the healthy and affected sides, mean muscle mass was 9.7 cm3/kg and 8.1 cm3/kg, and mean muscle HU values were 46.0 HU and 39.1 HU, respectively. Significant differences in muscle volume and quality were observed between the affected and healthy sides. On analyzing the function of various muscle groups, the TUG score showed a significant association with the gluteus maximum volume and the gluteus medius/minimus quality on the affected side.

CONCLUSION: Patients with HOA showed significant muscle atrophy and fatty degeneration in the affected pelvic and thigh regions. The gluteus maximum volume and gluteus medius/minimus quality were associated with early postoperative physical function. Preoperative rehabilitation targeting the gluteal muscles on the affected side could potentially enhance recovery of physical function in the early postoperative period.

PMID:39836355 | DOI:10.1007/s11548-025-03321-4

J Chem Phys. 2025 Jan 21;162(3):034120. doi: 10.1063/5.0236919.

ABSTRACT

Variational ab initio methods in quantum chemistry stand out among other methods in providing direct access to the wave function. This allows, in principle, straightforward extraction of any other observable of interest, besides the energy, but, in practice, this extraction is often technically difficult and computationally impractical. Here, we consider the electron density as a central observable in quantum chemistry and introduce a novel method to obtain accurate densities from real-space many-electron wave functions by representing the density with a neural network that captures known asymptotic properties and is trained from the wave function by score matching and noise-contrastive estimation. We use variational quantum Monte Carlo with deep-learning Ansätze to obtain highly accurate wave functions free of basis set errors and from them, using our novel method, correspondingly accurate electron densities, which we demonstrate by calculating dipole moments, nuclear forces, contact densities, and other density-based properties.

PMID:39836106 | DOI:10.1063/5.0236919

Aging (Albany NY). 2025 Jan 16;17. doi: 10.18632/aging.206190. Online ahead of print.

ABSTRACT

With the global population aging at an unprecedented rate, there is a need to extend healthy productive life span. This review examines how Deep Learning (DL) and Generative Artificial Intelligence (GenAI) are used in biomarker discovery, deep aging clock development, geroprotector identification and generation of dual-purpose therapeutics targeting aging and disease. The paper explores the emergence of multimodal, multitasking research systems highlighting promising future directions for GenAI in human and animal aging research, as well as clinical application in healthy longevity medicine.

PMID:39836094 | DOI:10.18632/aging.206190

Radiology. 2025 Jan;314(1):e233029. doi: 10.1148/radiol.233029.

ABSTRACT

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Background Detection and segmentation of lung tumors on CT scans are critical for monitoring cancer progression, evaluating treatment responses, and planning radiation therapy; however, manual delineation is labor-intensive and subject to physician variability. Purpose To develop and evaluate an ensemble deep learning model for automating identification and segmentation of lung tumors on CT scans. Materials and Methods A retrospective study was conducted between July 2019 and November 2024 using a large dataset of CT simulation scans and clinical lung tumor segmentations from radiotherapy plans. This dataset was used to train a 3D U-Net-based, image-multiresolution ensemble model to detect and segment lung tumors on CT scans. Model performance was evaluated on internal and external test sets composed of CT simulation scans and lung tumor segmentations from two affiliated medical centers, including single primary and metastatic lung tumors. Performance metrics included sensitivity, specificity, false positive rate, and Dice similarity coefficient (DSC). Model-predicted tumor volumes were compared with physician-delineated volumes. Group comparisons were made with Wilcoxon signed-rank test or one-way ANOVA. P < 0.05 indicated statistical significance. Results The model, trained on 1,504 CT scans with clinical lung tumor segmentations, achieved 92% sensitivity (92/100) and 82% specificity (41/50) in detecting lung tumors on the combined 150-CT scan test set. For a subset of 100 CT scans with a single lung tumor each, the model achieved a median model-physician DSC of 0.77 (IQR: 0.65-0.83) and an interphysician DSC of 0.80 (IQR: 0.72-0.86). Segmentation time was shorter for the model than for physicians (mean 76.6 vs. 166.1-187.7 seconds; p<0.001). Conclusion Routinely collected radiotherapy data were useful for model training. The key strengths of the model include a 3D U-Net ensemble approach for balancing volumetric context with resolution, robust tumor detection and segmentation performance, and the ability to generalize to an external site.

PMID:39835976 | DOI:10.1148/radiol.233029

J Chem Inf Model. 2025 Jan 21. doi: 10.1021/acs.jcim.4c02062. Online ahead of print.

ABSTRACT

Skin corrosion assessment is an essential toxicity end point that addresses safety concerns for topical dosage forms and cosmetic products. Previously, skin corrosion assessments required animal testing; however, differences in skin architecture and ethical concerns regarding animal models have fostered the advancement of alternative methods such as in silico and in vitro models. This study aimed to develop deep learning (DL) models based on recurrent neural networks (RNNs) for classifying skin corrosion of chemical compounds based on chemical language notation, molecular substructure, physicochemical properties, and a combination of these three properties called conjoint fingerprints. Simple RNN, long short-term memory, bidirectional long short-term memory (BiLSTM), gated recurrent units, and bidirectional gated recurrent units models, along with 11 molecular features, were employed to generate 55 RNN-based models. Applicability domain and permutation importance analysis were exploited for additional trustable prediction and explanation ability of the models, respectively. Our findings indicate that BiLSTM with conjoint features of MACCS keys and physicochemical descriptors is the most effective model with 84.3% accuracy, 89.8% area under the curve, and 57.6% Matthews correlation coefficient for the external test performance. Furthermore, our model accurately predicted the skin corrosion toxicity of all new and unseen compounds beyond our test set, highlighting prominent classification performance compared to existing skin corrosion models. This finding will contribute to the utilization of DL and conjoint characteristics of molecular structure to enhance the model's predictive capability for skin toxicity assessment.

PMID:39835935 | DOI:10.1021/acs.jcim.4c02062

Proc Natl Acad Sci U S A. 2025 Jan 28;122(4):e2415501122. doi: 10.1073/pnas.2415501122. Epub 2025 Jan 21.

ABSTRACT

Tropical cyclones (TCs), particularly those that rapidly intensify (RI), pose a significant threat due to the uncertainty in forecasting them. RI TC periods, which intensify by at least 13 m/s within 24 h, remain challenging to forecast accurately. Existing models achieve a probability of detection (POD) of 82.6% and a false alarm rate (FARate) of 27.2%. To address this, we developed a contrastive-based RI TC forecasting (RITCF-contrastive) model, utilizing satellite infrared imagery alongside atmospheric and oceanic data. The RITCF-contrastive model was tested on 1,149 TC periods in the Northwest Pacific from 2020 to 2021, achieving a POD of 92.3% and a FARate of 8.9%. RITCF-contrastive improves on previous models by addressing sample imbalance and incorporating TC structural features, leading to a 11.7% improvement in POD and a 3 times reduction in FARate compared to existing deep learning methods. The RITCF-contrastive model not only enhances RI TC forecasting but also offers a unique approach to forecasting these dangerous weather events.

PMID:39835899 | DOI:10.1073/pnas.2415501122

Electromagn Biol Med. 2025 Jan 21:1-18. doi: 10.1080/15368378.2024.2401540. Online ahead of print.

ABSTRACT

Brain tumors can cause difficulties in normal brain function and are capable of developing in various regions of the brain. Malignant tumours can develop quickly, pass through neighboring tissues, and extend to further brain regions or the central nervous system. In contrast, healthy tumors typically develop slowly and do not invade surrounding tissues. Individuals frequently struggle with sensory abnormalities, motor deficiencies affecting coordination, and cognitive impairments affecting memory and focus. In this research, Utilizing Phase-aware Composite Deep Neural Network Optimized with Coati Optimized Algorithm for Brain Tumor Identification Based on Magnetic resonance imaging (PACDNN-COA-BTI-MRI) is proposed. First, input images are taken from the brain tumour Dataset. To execute this, the input image is pre-processed using Multivariate Fast Iterative Filtering (MFIF) and it reduces the occurrence of over-fitting from the collected dataset; then feature extraction using Self-Supervised Nonlinear Transform (SSNT) to extract essential features like model, shape, and intensity. Then, the proposed PACDNN-COA-BTI-MRI is implemented in Matlab and the performance metrics Recall, Accuracy, F1-Score, Precision Specificity and ROC are analysed. Performance of the PACDNN-COA-BTI-MRI approach attains 16.7%, 20.6% and 30.5% higher accuracy; 19.9%, 22.2% and 30.1% higher recall and 16.7%, 21.9% and 30.8% higher precision when analysed through existing techniques brain tumor identification using MRI-Based Deep Learning Approach for Efficient Classification of Brain Tumor (MRI-DLA-ECBT), MRI-Based Brain Tumor Detection using Convolutional Deep Learning Methods and Chosen Machine Learning Techniques (MRI-BTD-CDMLT) and MRI-Based Brain Tumor Image Detection using CNN-Based Deep Learning Method (MRI-BTID-CNN) methods, respectively.

PMID:39835842 | DOI:10.1080/15368378.2024.2401540

J Acoust Soc Am. 2025 Jan 1;157(1):382-395. doi: 10.1121/10.0034857.

ABSTRACT

Underwater acoustic propagation is a complex phenomenon in the ocean environment. Traditional methods for calculating acoustic propagation loss rely on solving complex partial differential equations. Deep learning methods, leveraging their robust nonlinear approximation capabilities, can model various physical phenomena effectively, significantly reducing computation time and cost. Despite considerable advancements in the study of various inverse underwater acoustic problems, research focused on forward physical modeling is still nascent. This study proposes an end-to-end architecture for predicting underwater acoustic transmission loss (TL). This architecture employs a data-driven approach capable of swiftly and accurately predicting the complete acoustic field. It employs a U-Net model integrated with an adaptive multi-scale dilated module, named MultiScale-DUNet, which effectively predicts by assimilating multi-scale acoustic field information. It is demonstrated that the MultiScale-DUNet is capable of predicting acoustic TL in complex two-dimensional ocean environments within the end-to-end framework. The results indicate that the MultiScale-DUNet can rapidly predict the acoustic TL while maintaining high accuracy under computationally inexpensive conditions. This end-to-end technology for predicting underwater acoustic TL holds broad application prospects in fields such as underwater exploration and real-time underwater monitoring.

PMID:39835828 | DOI:10.1121/10.0034857

Hum Brain Mapp. 2025 Feb 1;46(2):e70136. doi: 10.1002/hbm.70136.

ABSTRACT

Magnetic susceptibility source separation (χ-separation), an advanced quantitative susceptibility mapping (QSM) method, enables the separate estimation of paramagnetic and diamagnetic susceptibility source distributions in the brain. Similar to QSM, it requires solving the ill-conditioned problem of dipole inversion, suffering from so-called streaking artifacts. Additionally, the method utilizes reversible transverse relaxation ( R 2 ' = R 2 * - R 2 $$ {R}_2^{\prime }={R}_2^{\ast }-{R}_2 $$ ) to complement frequency shift information for estimating susceptibility source concentrations, requiring time-consuming data acquisition for R 2 $$ {R}_2 $$ (e.g., multi-echo spin-echo) in addition to multi-echo GRE data for R 2 * $$ {R}_2^{\ast } $$ . To address these challenges, we develop a new deep learning network, χ-sepnet, and propose two deep learning-based susceptibility source separation pipelines, χ-sepnet- R 2 ' $$ {R}_2^{\prime } $$ for inputs with multi-echo GRE and multi-echo spin-echo (or turbo spin-echo) and χ-sepnet- R 2 * $$ {R}_2^{\ast } $$ for input with multi-echo GRE only. The neural network is trained using multiple head orientation data that provide streaking artifact-free labels, generating high-quality χ-separation maps. The evaluation of the pipelines encompasses both qualitative and quantitative assessments in healthy subjects, and visual inspection of lesion characteristics in multiple sclerosis patients. The susceptibility source-separated maps of the proposed pipelines delineate detailed brain structures with substantially reduced artifacts compared to those from the conventional regularization-based reconstruction methods. In quantitative analysis, χ-sepnet- R 2 ' $$ {R}_2^{\prime } $$ achieves the best outcomes followed by χ-sepnet- R 2 * $$ {R}_2^{\ast } $$ , outperforming the conventional methods. When the lesions of multiple sclerosis patients are classified into subtypes, most lesions are identified as the same subtype in the maps from χ-sepnet- R 2 ' $$ {R}_2^{\prime } $$ and χ-sepnet- R 2 * $$ {R}_2^{\ast } $$ (paramagnetic susceptibility: 99.6% and diamagnetic susceptibility: 98.4%; both out of 250 lesions). The χ-sepnet- R 2 * $$ {R}_2^{\ast } $$ pipeline, which only requires multi-echo GRE data, has demonstrated its potential to offer broad clinical and scientific applications, although further evaluations for various diseases and pathological conditions are necessary.

PMID:39835664 | DOI:10.1002/hbm.70136

Mol Biol Evol. 2025 Jan 21:msaf017. doi: 10.1093/molbev/msaf017. Online ahead of print.

ABSTRACT

Bats have adapted to pathogens through diverse mechanisms, including increased resistance - rapid pathogen elimination, and tolerance - limiting tissue damage following infection. In the Egyptian fruit bat (an important model in comparative immunology) several mechanisms conferring disease tolerance were discovered, but mechanisms underpinning resistance remain poorly understood. Previous studies on other species suggested that elevated basal expression of innate immune genes may lead to increased resistance to infection. Here, we test whether such transcriptional patterns occur in Egyptian fruit bat tissues through single-cell and spatial transcriptomics of gut, lung and blood cells, comparing gene expression between bat, mouse and human. Despite numerous recent loss and expansion events of interferons in the bat genome, interferon expression and induction are remarkably similar to that of mouse. In contrast, central complement system genes are highly and uniquely expressed in key regions in bat lung and gut epithelium, unlike in human and mouse. Interestingly, the unique expression of these genes in the bat gut is strongest in the crypt, where developmental expression programs are highly conserved. The complement system genes also evolve rapidly in their coding sequence across the bat lineage. Finally, the bat complement system displays strong hemolytic activity. Together, these results indicate a distinctive transcriptional divergence of the complement system, which may be linked to bat resistance, and highlight the intricate evolutionary landscape of bat immunity.

PMID:39836373 | DOI:10.1093/molbev/msaf017

Appl Microbiol Biotechnol. 2025 Jan 21;109(1):14. doi: 10.1007/s00253-024-13390-1.

ABSTRACT

Butenyl-spinosyn, derived from Saccharopolyspora pogona, is a broad-spectrum and effective bioinsecticide. However, the regulatory mechanism affecting butenyl-spinosyn synthesis has not been fully elucidated, which hindered the improvement of production. Here, a high-production strain S. pogona H2 was generated by Cobalt-60 γ-ray mutagenesis, which showed a 2.7-fold increase in production compared to the wild-type strain S. pogona ASAGF58. A comparative transcriptomic analysis between S. pogona ASAGF58 and H2 was performed to elucidate the high-production mechanism that more precursors and energy were used to synthesize of butenyl-spinosyn. Fortunately, a PurR family transcriptional regulator TF00350 was discovered. TF00350 overexpression strain RS00350 induced morphological differentiation and butenyl-spinosyn production, ultimately leading to a 5.5-fold increase in butenyl-spinosyn production (141.5 ± 1.03 mg/L). Through transcriptomics analysis, most genes related to purine metabolism pathway were downregulated, and the butenyl-spinosyn biosynthesis gene was upregulated by increasing the concentration of c-di-GMP and decreasing the concentration of c-di-AMP. These results provide valuable insights for further mining key regulators and improving butenyl-spinosyn production. KEY POINTS: • A high production strain of S. pogona H2 was obtained by 60Co γ-ray mutagenesis. • Positive regulator TF00350 identified by transcriptomics, increasing butenyl-spinosyn production by 5.5-fold. • TF00350 regulated of butenyl-spinosyn production by second messengers.

PMID:39836216 | DOI:10.1007/s00253-024-13390-1

Biochem Soc Trans. 2025 Jan 21:BST20240678. doi: 10.1042/BST20240678. Online ahead of print.

ABSTRACT

Many prokaryotic and eukaryotic cells store inorganic phosphate in the form of polymers called polyphosphate (polyP). There has been an explosion of interest in polyP over the past decade, in part due to newly suggested roles related to diverse aspects of human health. The physical interaction of polyP chains with specific proteins has been proposed to regulate cellular homeostasis and modulate signaling pathways in response to environmental changes. Recently, several studies have challenged existing models for how polyP interacts with its protein targets, while identifying new motifs that are capable of binding to polyP. In this review, we summarize these findings, delineate the functional implications for polyP-protein interactions at the molecular level, and define open questions that should be addressed to propel the field forward.

PMID:39836110 | DOI:10.1042/BST20240678

Clin Transl Gastroenterol. 2025 Jan 21. doi: 10.14309/ctg.0000000000000803. Online ahead of print.

ABSTRACT

INTRODUCTION: X842 is a new type of gastric acid-suppressing agent with a rapid onset of action and a long duration of effect. We aim to investigate the efficacy and safety of different doses of X842 versus lansoprazole in the treatment of patients with erosive esophagitis (EE).

METHODS: This phase 2 study included 90 patients with EE (Los Angeles grades A-D) who were randomized (1:1:1) to receive oral low-dose X842 (50 mg/day, n=31), high-dose X842 (100 mg/day, n=31), or lansoprazole (30 mg/day, n=30) for 4 weeks. The main efficacy endpoint was the EE healing rate, which was the proportion of patients who achieved endoscopic healing after 4 weeks of treatment.

RESULTS: For ITT analysis, the EE healing rates at 4 weeks were 93.6% (29/31), 79.3% (23/29), and 80.0% (24/30) for the X842 50 mg, the X842 100 mg and the lansoprazole 30 mg groups. For PP analysis, the EE healing rates at 4 weeks were 93.6% (29/31), 80.8% (21/26), and 82.1% (23/28) in the three groups, respectively. The EE healing rate did not significantly differ among the three groups in either the ITT (p = 0.2351) or PP (p = 0.3320) analysis. The incidence of drug-related treatment-emergent adverse events (TEAEs) did not differ among groups. No severe drug-related TEAEs occurred in the X842 group.

CONCLUSIONS: Our findings confirmed that X842 had efficacy and a favourable safety profile similar to those of lansoprazole. Therefore, X842, a novel P-CAB, is expected to become a promising therapeutic agent for EE.

PMID:39836012 | DOI:10.14309/ctg.0000000000000803