bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating the role of DNA methyltransferases in trophoblast fusion and preeclampsia development: Insights from methylation‐regulated genes
Authors: Yang You‐Fu , Li Zhuo‐Hang , Liu Tai‐Hang , Li Cong , Xie You‐Long , Ge Lu‐Xing , Tang Jing , Li Fang‐Fang , Luo Xin , Fu Li‐Juan , Ding Yu‐Bin
Published: June 2024

The etiology of preeclampsia (PE), a complex and multifactorial condition, remains incompletely understood. DNA methylation, which is primarily regulated by three DNA methyltransferases (DNMTs), DNMT1, DNMT3A, and DNMT3B, plays a vital role in early embryonic development and trophectoderm differentiation. Yet, how DNMTs modulate trophoblast fusion and PE development remains unclear. In this study, we found that the DNMTs expression was downregulated during trophoblast cells fusion. Downregulation of DNMTs was observed during the reconstruction of the denuded syncytiotrophoblast (STB) layer of placental explants. Additionally, overexpression of DNMTs inhibited trophoblast fusion. Conversely, treatment with the DNA methylation inhibitor 5‐aza‐CdR decreased the expression of DNMTs and promoted trophoblast fusion. A combined analysis of DNA methylation data and gene transcriptome data obtained from the primary cytotrophoblasts (CTBs) fusion process identified 104 potential methylation‐regulated differentially expressed genes (MeDEGs) with upregulated expression due to DNA demethylation, including CD59, TNFAIP3, SDC1, and CDK6. The transcription regulation region (TRR) of TNFAIP3 showed a hypomethylation with induction of 5‐aza‐CdR, which facilitated CREB recruitment and thereby participated in regulating trophoblast fusion. More importantly, clinical correlation analysis of PE showed that the abnormal increase in DNMTs may be involved in the development of PE. This study identified placental DNA methylation‐regulated genes that may contribute to PE, offering a novel perspective on the role of epigenetics in trophoblast fusion and its implication in PE development.
Deep learning and digital pathology powers prediction of HCC development in steatotic liver disease
Authors: Nakatsuka Takuma , Tateishi Ryosuke , Sato Masaya , Hashizume Natsuka , Kamada Ami , Nakano Hiroki , Kabeya Yoshinori , Yonezawa Sho , Irie Rie , Tsujikawa Hanako , Sumida Yoshio , Yoneda Masashi , Akuta Norio , Kawaguchi Takumi , Takahashi Hirokazu , Eguchi Yuichiro , Seko Yuya , Itoh Yoshito , Murakami Eisuke , Chayama Kazuaki , Taniai Makiko , Tokushige Katsutoshi , Okanoue Takeshi , Sakamoto Michiie , Fujishiro Mitsuhiro , Koike Kazuhiko
Published: June 2024

Background and Aims:

Identifying patients with steatotic liver disease who are at a high risk of developing HCC remains challenging. We present a deep learning (DL) model to predict HCC development using hematoxylin and eosin-stained whole-slide images of biopsy-proven steatotic liver disease.

Approach and Results:

We included 639 patients who did not develop HCC for ≥7 years after biopsy (non-HCC class) and 46 patients who developed HCC <7 years after biopsy (HCC class). Paired cases of the HCC and non-HCC classes matched by biopsy date and institution were used for training, and the remaining nonpaired cases were used for validation. The DL model was trained using deep convolutional neural networks with 28,000 image tiles cropped from whole-slide images of the paired cases, with an accuracy of 81.0% and an AUC of 0.80 for predicting HCC development. Validation using the nonpaired cases also demonstrated a good accuracy of 82.3% and an AUC of 0.84. These results were comparable to the predictive ability of logistic regression model using fibrosis stage. Notably, the DL model also detected the cases of HCC development in patients with mild fibrosis. The saliency maps generated by the DL model highlighted various pathological features associated with HCC development, including nuclear atypia, hepatocytes with a high nuclear-cytoplasmic ratio, immune cell infiltration, fibrosis, and a lack of large fat droplets.

Conclusions:

The ability of the DL model to capture subtle pathological features beyond fibrosis suggests its potential for identifying early signs of hepatocarcinogenesis in patients with steatotic liver disease.
The impact of premature rupture of membrane on neonatal outcomes in infants born at 34 weeks gestation or later
Authors: Su Chih-Ting , Chen Wei-Yu , Tsao Pei-Chen , Lee Yu-Sheng , Jeng Mei-Jy
Published: June 2024

Background:

Premature rupture of membranes (PROMs) is a known risk for adverse neonatal outcomes, often leading to neonatal hospitalization due to suspected perinatal infection or other issues. This study assesses PROM’s clinical impact on neonatal outcomes in infants born at 34 weeks of gestation or later.

Methods:

We studied hospitalized neonates born between December 2018 and November 2019, with gestational ages of 34 weeks or more and PROM diagnosis. We extracted patient data from clinical records, including demographics, maternal history, medical profiles, and neonatal outcomes. Neonates were categorized based on symptoms, PROM duration, neonatal intensive care unit (NICU) stay, and respiratory support. Data underwent thematic analysis.

Results:

Of 275 neonates, the average PROM duration was 7.9 ± 8.1 hours, with 247 cases (89.8%) showing symptoms. Among them, 34 (12.4%) had PROM lasting over 18 hours, 48 (17.5%) were born prematurely, and 79 (28.7%) required intensive care. Symptomatic neonates had significantly higher rates of needing intensive care, respiratory support, prolonged antibiotics, and extended hospitalization (p < 0.05). NICU stays (≥3 days) were significantly associated with prematurity (odds ratio [OR] = 5.49; 95% CI, 2.39-12.60) and an initial pH level <7.25 (OR = 3.35; 95% CI, 1.46-7.68). Extended respiratory support (≥3 days) was significantly correlated with tocolysis ≥7 days (OR = 13.20; 95% CI, 3.94-44.20), Apgar score <7 at 1 minute after birth (OR = 4.28; 95% CI, 1.67-10.97), and inadequate intrapartum antibiotic prophylaxis (IAP) (OR = 2.34; 95% CI, 1.04-5.23).

Conclusion:

Neonates born at or after 34 weeks of gestation with PROM should undergo vigilant monitoring if early symptoms (<24 hours) manifest. Risk factors for requiring NICU care or extended respiratory support (≥3 days) include prematurity, low initial pH (<7.25), prolonged tocolysis requirement (≥7 days), an Apgar score below 7 at 1 minute, and inadequate IAP.
Recent developments in cancer diagnosis and treatment using nanotechnology
Authors: Ouled Ltaief Olfa , Ben Amor Ilham , Hemmami Hadia , Hamza Wiem , Zeghoud Soumeia , Ben Amor Asma , Benzina Mourad , Alnazza Alhamad Ali
Published: June 2024

The article provides an insightful overview of the pivotal role of nanotechnology in revolutionizing cancer diagnosis and treatment. It discusses the critical importance of nanoparticles in enhancing the accuracy of cancer detection through improved imaging contrast agents and the synthesis of various nanomaterials designed for oncology applications. The review broadly classifies nanoparticles used in therapeutics, including metallic, magnetic, polymeric, and many other types, with an emphasis on their functions in drug delivery systems for targeted cancer therapy. It details targeting mechanisms, including passive and intentional targeting, to maximize treatment efficacy while minimizing side effects. Furthermore, the article addresses the clinical applications of nanomaterials in cancer treatment, highlights prospects, and addresses the challenges of integrating nanotechnology into cancer treatment.
Frantz’s tumor as incidental finding during Heller myotomy for achalasia: case report and review of literature
Authors: Printes Thaís Regina Moreira , de Castro Gustavo Lopes , Rabelo Delon Calixto , da Silva Neto Rubem Alves , da Silva Junior Rubem Alves
Published: June 2024

Introduction:

Solid pseudopapillary tumor is a low-grade malignancy of the pancreas and predominantly affects young women. This neoplasm is a rare pancreatic entity with vague clinical presentation. Diagnosis is often incidental through imaging or even during surgical approach for another condition.

Case presentation:

A 22-year-old Brazilian female with gastrointestinal symptoms was diagnosed with achalasia and underwent Heller myotomy. Intraoperatory findings included an enlarging mass in the distal pancreas. During follow-up for the surgical approach of achalasia, a hypothesis of Frantz’s tumor was stated, and spleen-preserving distal pancreatectomy was performed.

Discussion:

The pathological pathways of Frantz’s tumor is still unclear, and its connection with chromosomal abnormalities is under investigation. Although the tumor has been reclassified over the years to solid pseudopapillary tumor, surgical resection remains the standard treatment.

Conclusion:

Despite a surgical challenge, surgery presents a great prognosis in these patients and long-term survival. High suspicion and proper investigation are fundamental to diagnosis and early treatment.
Knowledge, attitude, and practice of artificial intelligence applications in medicine among physicians in Sudan: a national cross-sectional survey
Authors: Hammad Jaber Amin Mohammed , Abdelmonim Gasm Alseed Fadlalmoula Gasm Alseed , Awadalla Mohamed Elhassan Elmahi Musab , hatim Khalid Alrabee Noon , Hemmeda Lina , Haydar Awad Mohammed , Mustafa Ahmed Ghassan E. , Abbasher Hussien Mohamed Ahmed Khabab
Published: June 2024

Background and aims:

Artificial intelligence (AI) has emerged as a rapidly developing tool within the medical landscape, globally aiding in diagnosis and healthcare management. However, its integration within healthcare systems remains varied across different regions. In Sudan, there exists a burgeoning interest in AI potential applications within medicine. This study aims to evaluate the knowledge, attitudes, and practices of AI applications in medicine among physicians in Sudan.

Methods:

The authors conducted a web-based survey cross-sectional analytical study using an online questionnaire-based survey regarding demographic details, knowledge, attitudes, and practice of AI distributing through various e-mail listings and social media platforms. A sample of 825 Physicians including doctors in Sudan with different ranks and specialties were selected using the convenient non-probability sampling technique.

Result:

Out of 825 Physicians, 666 (80.7%) of Physicians have previous knowledge about AI. However, only a small number 123 (14.9%) were taught about AI during their time in medical school, even fewer, just 120 (14.5%) had AI-related lessons in their training program. Regarding attitude, 675 (81.8%) agree that AI is very important in medicine, almost the same number, 681 (82.6%) support the idea of teaching AI in medical schools. Practically, 535 (64.8%) of doctors, think that should get special training in using AI tools in healthcare. Excitingly 651 (78.9%) of physicians are interested in working with AI in future. Based on different ranks of doctors toward AI; Medical Officers exhibited the highest proportion at (32.7%) of knowledge and understanding of AI concepts, followed by House Officers at (16.7%) (p=0.076); regarding attitude, Medical Officers demonstrated the highest (31.6%) favorable attitude, followed by House Officers at (17.5%) (p=0.229); In practice also, Medical Officer showed the highest portion (28.0%) among participants (p=0.129).

Conclusion:

While there is a positive attitude and some level of AI practice, there remains a considerable gap in knowledge that needs addressing.
Congenital colloid cyst with astigmatism in adult male patient: a rare case report
Authors: Dawabsheh Salwa H. , Abed Samamqa Salma , Kawazbeh Waleed N. , Mohammad Basel , Sallam Qasim M. , Massoud Haya , Dway Ali , Awaysa Asala Mohammad , Al- Karaja Layth
Published: June 2024

Introduction and importance:

Colloid cysts are rare brain tumors that can cause headaches, memory problems, and vision issues. Early diagnosis and treatment are crucial to prevent complications.

Case presentation:

The authors report a case of a patient in their 20s with a 2-year history of headaches and blurry vision. A computed tomography (CT) scan revealed a colloid cyst in the third ventricle. The patient was diagnosed with astigmatism and managed with corrective lenses and regular CT scans.

Clinical discussion:

The patient’s astigmatism may be linked to the colloid cyst, potentially due to migraines triggered by the cyst’s location. Further research is needed to understand this relationship.

Conclusion:

This case highlights the potential for colloid cysts to contribute to vision problems. Careful evaluation and individualized management are essential for patients with colloid cysts and vision disturbances.
Cathepsin B causes trogocytosis-mediated CAR T cell dysfunction
Authors: Dietze Kenneth A , Nguyen Kiet , Pathni Aashli , Fazekas Frank , Baker Jillian M , Gebru Etse , Wang Alexander , Sun Wenxiang , Rosati Ethan , Lum David , Rapoport Aaron P , Fan Xiaoxuan , Atanackovic Djordje , Upadhyaya Arpita , Luetkens Tim
Published: June 2024

Chimeric antigen receptor (CAR) T cell therapy has shown remarkable efficacy in cancer treatment. Still, most patients receiving CAR T cells relapse within 5 years of treatment. CAR-mediated trogocytosis (CMT) is a potential tumor escape mechanism in which cell surface proteins transfer from tumor cells to CAR T cells. CMT results in the emergence of antigen-negative tumor cells, which can evade future CAR detection, and antigen-positive CAR T cells, which has been suggested to cause CAR T cell fratricide and exhaustion. Whether CMT indeed causes CAR T cell dysfunction and the molecular mechanisms conferring CMT remain unknown. Using a selective degrader of trogocytosed antigen in CAR T cells, we show that the presence of trogocytosed antigen on the CAR T cell surface directly causes CAR T cell fratricide and exhaustion. By performing a small molecule screening using a custom high throughput CMT-screening assay, we found that the cysteine protease cathepsin B (CTSB) is essential for CMT and that inhibition of CTSB is sufficient to prevent CAR T cell fratricide and exhaustion. Our data demonstrate that it is feasible to separate CMT from cytotoxic activity and that CAR T cell persistence, a key factor associated with clinical CAR T cell efficacy, is directly linked to CTSB activity in CAR T cells.
Therapeutic expression of RAS Degrader RRSP in Pancreatic Cancer via Nanocarrier-mediated mRNA delivery
Authors: Escher Taylor E. , Yuk Simseok A. , Qian Yuan , Stubbs Caleb K. , Scott Evan A. , Satchell Karla J.F.
Published: June 2024

Abstract Figure

Graphical Abstract:

Synthetic nanocarriers packaged with mRNA are used to express the RAS-specific protease RRSP in cancer cells resulting in cell death and tumor shrinkage.

About one-third of all human cancers encode abnormal RAS proteins locked in a constitutively activated state to drive malignant transformation and uncontrolled tumor growth. Despite progress in development of small molecules for treatment of mutant KRAS cancers, there is a need for a pan-RAS inhibitor that is effective against all RAS isoforms and variants and that avoids drug resistance. We have previously shown that the naturally occurring bacterial enzyme RAS/RAP1-specific endopeptidase (RRSP) is a potent RAS degrader that can be re-engineered as a biologic therapy to induce regression of colorectal, breast, and pancreatic tumors. Here, we have developed a strategy for in vivo expression of this RAS degrader via mRNA delivery using a synthetic nonviral gene delivery platform composed of the poly(ethylene glycol)-b-poly(propylene sulfide) (PEG-b-PPS) block copolymer conjugated to a dendritic cationic peptide (PPDP2). Using this strategy, PPDP2 is shown to deliver mRNA to both human and mouse pancreatic cells resulting in RRSP gene expression, activity, and loss of cell proliferation. Further, pancreatic tumors are reduced with residual tumors lacking detectable RAS and phosphorylated ERK. These data support that mRNA-loaded synthetic nanocarrier delivery of a RAS degrader can interrupt the RAS signaling system within pancreatic cancer cells while avoiding side effects during therapy.
Topically applied thyroid hormones stimulate hair growth in organ-cultured human scalp skin
Authors: Gherardini Jennifer , Akhundlu Aysun , Gompels Matthew , Verbinnen Andrew , Velasco Sergi , Knie Ulrich , Kassir Ramtin , Cheret Jeremy , Paus Ralf
Published: June 2024

We have previously shown that the thyroid hormones triiodothyronine (T3) and thyroxine (T4) prolong anagen, mitigate stem cell apoptosis, and stimulate mitochondrial functions in microdissected human scalp HFs ex vivo. To circumvent the systemic adverse effects of T3/T4, we have asked in the current pilot study whether topically applied T3/T4 retains hair growth-promoting properties. To prove this, we have topically treated healthy full-thickness human scalp skin with T3 (1, 10nM) and T4 (1, 10μM) for six days in serum-free organ culture, using an HF-targeting vehicle that contains only FDA-approved ingredients. This showed that, at distinct doses, topical T3 and T4 significantly increased the percentage of HFs in anagen, decreased the percentage of proliferative (Ki-67+) cells in the hair matrix, did not promote melanogenesis (as measured by quantitative Warthin-Starry histochemistry), and significantly increased keratin 15 expression in the bulge. Finally, T3 and T4, at low concentrations, increase the expression of the hair growth promoters IGF-1 and FGF-7. The lower concentration of T3 and both of T4 also significantly increases the number of CD31+ endothelial cells, suggesting a pro-angiogenic effect, which is also important for hair growth promotion. These preliminary results strongly suggest that topically applied thyroid hormones promote hair growth in intact human scalp on multiple levels ex vivo. This invites the intermittent pulse application of topical T3 and T4 as a novel therapeutic intervention for managing hair loss disorders associated with telogen effluvium, such as androgenetic alopecia.
Detection and classification of long terminal repeat sequences in plant LTR-retrotransposons and their analysis using explainable machine learning
Authors: Horvath Jakub , Jedlicka Pavel , Kratka Marie , Kubat Zdenek , Kejnovsky Eduard , Lexa Matej
Published: June 2024

Background

Long terminal repeats (LTRs) represent important parts of LTR retrotransposons and retroviruses found in high copy numbers in a majority of eukaryotic genomes. LTRs contain regulatory sequences essential for the life cycle of the retrotransposon. Previous experimental and sequence studies have provided only limited information about LTR structure and composition, mostly from model systems. To enhance our understanding of these key compounds, we focused on the contrasts between LTRs of various retrotransposon families and other genomic regions. Furthermore, this approach can be utilized for the classification and prediction of LTRs.

Results

We used machine learning methods suitable for DNA sequence classification and applied them to a large dataset of plant LTR retrotransposon sequences. We trained three machine learning models using (i) traditional model ensembles (Gradient Boosting - GBC), (ii) hybrid CNN-LSTM models, and (iii) a pre-trained transformer-based model (DNABERT) using k-mer sequence representation. All three approaches were successful in classifying and isolating LTRs in this data, as well as providing valuable insights into LTR sequence composition. The best classification (expressed as F1 score) achieved for LTR detection was 0.85 using the CNN-LSTM hybrid network model. The most accurate classification task was superfamily classification (F1=0.89) while the least accurate was family classification (F1=0.74). The trained models were subjected to explainability analysis. SHAP positional analysis identified a mixture of interesting features, many of which had a preferred absolute position within the LTR and/or were biologically relevant, such as a centrally positioned TATA-box, and TG..CA patterns around both LTR edges.

Conclusions

Our results show that the models used here recognized biologically relevant motifs, such as core promoter elements in the LTR detection task, and a development and stress-related subclass of transcription factor binding sites in the family classification task. Explainability analysis also highlighted the importance of 5’- and 3’-edges in LTR identity and revealed need to analyze more than just dinucleotides at these ends. Our work shows the applicability of machine learning models to regulatory sequence analysis and classification, and demonstrates the important role of the identified motifs in LTR detection.
TLCellClassifier: Machine Learning Based Cell Classification for Bright-Field Time-Lapse Images
Authors: Jiang Qibing , Sudalagunta Praneeth Reddy , Meads Mark , Zhao Xiaohong , Achille Alexandra , Noyes David , Silva Maria , Canevarolo Rafael Renatino , Shain Ken , Silva Ariosto , Zhang Wei
Published: June 2024

Immunotherapies have shown promising results in treating patients with hematological malignancies like multiple myeloma, which is an incurable but treatable bone marrow-resident plasma cell cancer. Choosing the most efficacious treatment for a patient remains a challenge in such cancers. However, pre-clinical assays involving patient-derived tumor cells co-cultured in anex vivoreconstruction of immune-tumor micro-environment have gained considerable notoriety over the past decade. Such assays can characterize a patient’s response to several therapeutic agents including immunotherapies in a high-throughput manner, where bright-field images of tumor (target) cells interacting with effector cells (T cells, Natural Killer (NK) cells, and macrophages) are captured once every 30 minutes for upto six days. Cell detection, tracking, and classification of thousands of cells of two or more types in each frame is bound to test the limits of some of the most advanced computer vision tools developed to date and requires a specialized approach. We propose TLCellClassifier (time-lapse cell classifier) for live cell detection, cell tracking, and cell type classification, with enhanced accuracy and efficiency obtained by integrating convolutional neural networks (CNN), metric learning, and long short-term memory (LSTM) networks, respectively. State-of-the-art computer vision software like KTH-SE and YOLOv8 are compared with TLCellClassifier, which shows improved accuracy in detection (CNN) and tracking (metric learning). A two-stage LSTM-based cell type classification method is implemented to distinguish between multiple myeloma (tumor/target) cells and macrophages/monocytes (immune/effector cells). Validation of cell type classification was done both using synthetic datasets andex vivoexperiments involving patient-derived tumor/immune cells.

Availability and implementation

https://github.com/QibingJiang/cell classification ml
Durable Antimicrobial Microstructure Surface (DAMS) Enabled by 3D-Printing and ZnO Nanoflowers
Authors: Yuqing FNU , Zhang Shuhuan , Peng Ruonan , Silva Justin , Ernst Olivia , Lapizco-Encinas Blanca H , Liu Rui , Du Ke
Published: June 2024

A.

Numerous studies have been trying to create nanomaterials based antimicrobial surfaces to combat the growing bacterial infection problems. Mechanical durability has become one of the major challenges to applying those surfaces in real life. In this study, we demonstrate the Durable Antimicrobial Microstructures Surface (DAMS) consisting of DLP 3D printed microstructures and zinc oxide (ZnO) nanoflowers. The microstructures serve as a protection armor for the nanoflowers during abrasion. The antimicrobial ability was tested by immersing in 2E8 CFU/mLEscherichia coli(E. coli) suspension and then evaluated using electron microscopy. Compared to the bare control, our results show that the DAMS reduces bacterial coverage by more than 90% after 12 hrs of incubation and approximately 50% after 48 hrs of incubation before abrasion. Importantly, bacterial coverage is reduced by approximately 50% after 2 min of abrasion with a tribometer, and DAMS remains effective even after 6 min of abrasion. These findings highlight the potential of DAMS as an affordable, scalable, and durable antimicrobial surface for various biomedical applications.
Drug combinations with apoptosis pathway targeted agents alrizomadlin, pelcitoclax, and dasminapant in multi-cell type tumor spheroids
Authors: Coussens Nathan P. , Dexheimer Thomas S. , Silvers Thomas , Sanchez Phillip R. , Takebe Naoko , Doroshow James H. , Teicher Beverly A.
Published: June 2024

Apoptosis, or programmed cell death, plays a critical role in maintaining tissue homeostasis by eliminating damaged or abnormal cells. Dysregulation of apoptosis pathways is a hallmark of cancer, allowing malignant cells to evade cell death and proliferate uncontrollably. Targeting apoptosis pathways has emerged as a promising therapeutic strategy in cancer treatment, aiming to restore the balance between cell survival and death. In this context, the MDM2 inhibitor alrizomadlin, the Bcl-2/Bcl-xL inhibitor pelcitoclax, and the IAP family inhibitor dasminapant were evaluated both individually and in combination with standard of care and investigational anticancer small molecules with a spheroid model of solid tumors. The multi-cell type tumor spheroids were grown from endothelial cells and mesenchymal stem cells combined with human malignant cells that were either established or patient-derived cell lines from the NCI Patient- Derived Models Repository. The malignant cell lines were derived from a range of solid tumors including uterine carcinosarcoma, synovial sarcoma, rhabdomyosarcoma, soft tissue sarcoma, malignant fibrous histiocytoma, malignant peripheral nerve sheath tumor (MPNST), pancreas, ovary, colon, breast, and small cell lung cancer. Interactions were observed from combinations of the apoptosis pathway targeted agents. Additionally, interactions were observed from combinations of the apoptosis pathway targeted agents with other agents, including PARP inhibitors, the XPO1 inhibitor eltanexor, and the PI3K inhibitor copanlisib. Enhanced activity was also observed from combinations of the apoptosis pathway targeted agents with MAPK pathway targeted agents, including the MEK inhibitor cobimetinib as well as adagrasib and MRTX1133, which specifically target the KRAS G12C and G12D variants, respectively.

SIGNIFICANCE

Multi-cell type tumor spheroids grown from normal and patient-derived malignant cell lines were screened to identify potentially efficacious combinations with the investigational agents alrizomadlin, pelcitoclax or dasminapant that target cell death pathways. This article highlights novel combinations with FDA approved drugs including eltanexor, cobimetinib and copanlisib.
Zinc-starved Brassicaceae Plants Secrete Peptides that Induce Root Expansion
Authors: Niehs Sarah P. , Rajniak Jakub , Johnson Anna , Wengier Diego L. , Sattely Elizabeth S.
Published: June 2024

Zinc (Zn) deficiency is recognized as a global crisis as it is observed in half of all agricultural soils. However, the molecular mechanisms that drive plant physiological responses to soil Zn deficiency are not well understood. We used an untargeted metabolomics approach to search for metabolites exuded from roots during Zn deficiency stress, which led to the discovery of a collection of secreted small defensin-like peptides inArabidopsis thaliana(named Zinc-Deficiency Responsive Peptides (ZDRPs)). Phylogenetic analysis and untargeted metabolomics revealed ZDRPs in at least eleven accessions ofA. thalianaand nine members of the Brassicaceae family. Analysis ofArabidopsisgene mutants and overexpressing lines, in combination with chemical complementation experiments, unveiled a critical role of these peptides in plant root growth. We hypothesize that Brassicaceae secreted peptides enable plants to expand their root mass to reach Zn-rich soil layers and optimize Zn uptake. These data reveal a critical relationship between plant survival, Zn status, root morphology and peptide production. Taken together, our results expand our knowledge regarding micronutrient deficiency responses in plants and could enable in engineering approaches to make plants more resilient to low Zn conditions.

Significance

Zinc deficiency is the most abundant micronutrient deficiency affecting about 50% of arable lands thus presenting a high burden for plant health and agriculture globally. In this study, we reveal a metabolic strategy by Brassicaceae to deal with low Zn concentrations. We characterize the role of peptides expressed upon zinc deficiency in a variety of important crop plants. The discovery of a cryptic class of peptides that are made by plant roots specifically suffering from Zn deficiency provides critical insight into the molecular mechanisms by which plants dynamically acclimate to nutrient-limited soils. The identification of peptides actively secreted by zinc-deprived plants has translational value for sustainable agriculture, human health, and bioengineering approaches to enable tolerance to low zinc.
Perinatal brain group 3 innate lymphoid cells are involved in the formation of murine dural lymphatics
Authors: del Rio Serrato Alba , Hernández Borja Latorre , Bartl Evie , Stehle Christina , Hölsken Oliver , Diefenbach Andreas , Romagnani Chiara , Infante-Duarte Carmen
Published: June 2024

The central nervous system (CNS) contains a pool of innate lymphoid cells (ILCs) of unclear composition and functionality and unknown origin. Here, we demonstrate that group 1 ILCs (inc. ex-ILC3s) and ILC2s are resident cells with low proliferative capacities and subtype specific CNS compartmentalization. We show for the first time that CNS ILC seeding and niche establishment occurs during early life and is initiated by both, ILC progenitors-like PLFZ+PD- 1+cells and lineage committed ILCs. While group 1 ILCs and RORγt+ILC3s were found within the embryonic and postnatal brain, ILC2s reached the CNS after birth and were predominantly localized within the dura mater, proving early regional distribution. Interestingly, RORγt+ILC3s were only detected perinatally and vanished from the CNS as an outcome of decreased turnover andin situILC3-to-ILC1 conversion. Remarkably, we showed that perinatal RORγt+ILC3s are required for the correct development of the lymphatic vessels within the dura.
Creating simple predictive models in ecology, conservation and environmental policy based on Bayesian belief networks
Authors: Dominguez Almela Victoria , Croker Abigail R , Stafford Richard
Published: June 2024

Predictive models are often complex to produce and interpret, yet can offer valuable insights for management, conservation and policy-making through relatively simple approaches. We demonstrate that by using straightforward concepts to describe interactions between model components, predictive models can be effectively constructed using basic spreadsheet tools. Using a new R package (BBNet), these models can be analysed, visualised, and sensitivity tested to assess how information flows through the system’s components. The models are based on Bayesian belief networks (BBN) but adapted to overcome some of the complexity and shortcomings of the traditional BBN approach. The models are not fully quantitative, but outcomes between different modelled scenarios can be considered ordinally (i.e. ranked). Parameterisation of models can also be through data, literature, expert opinion, or questionnaires and surveys of opinion. While we have focussed on the use of the models in environmental and ecological problems (including with links to management and social outcomes), their application does not need to be restricted to these disciplines, and use in financial systems, molecular biology, political sciences and many other disciplines are possible.
Label-Free Optical Mapping for Large-Area Biomechanical Dynamics of Multicellular Systems
Authors: Lin Yen-Ju , Tan Xing Haw Marvin , Wang Yijie , Chung Pei-Shan , Zhang Xiang , Wu Ting-Hsiang , Wu Tung-Yu , Deb Arjun , Chiou Pei-Yu
Published: June 2024

Mapping cellular activities over large areas is crucial for understanding the collective behaviors of multicellular systems. Biomechanical properties, such as cellular traction force, serve as critical regulators of physiological states and molecular configurations. However, existing technologies for mapping large-area biomechanical dynamics are limited by the small field of view and scanning nature. To address this, we propose a novel platform that utilizes a vast number of optical diffractive elements for mapping large-area biomechanical dynamics. This platform achieves a field-of-view of 10.6 mm X 10.6 mm, a three-orders-of-magnitude improvement over traditional traction force microscopy. Transient mechanical waves generated by monolayer neonatal rat ventricular myocytes were captured with high spatiotemporal resolution (130 fps and 20 µm for temporal and spatial resolution, respectively). Furthermore, its label-free nature allows for long-term observations extended to a week, with minimal disruption of cellular functions. Finally, simultaneous measurements of calcium ions concentrations and biomechanical dynamics are demonstrated.
Performance evaluation of adaptive introgression classification methods
Authors: Romieu Jules , Camarata Ghislain , Crochet Pierre-André , de Navascués Miguel , Leblois Raphaël , Rousset François
Published: June 2024

Introgression, the incorporation of foreign variants through hybridization and repeated backcross, is increasingly being studied for its potential evolutionary consequences, one of which is adaptive introgression (AI). In recent years, several statistical methods have been proposed for the detection of loci that have undergone adaptive introgression. Most of these methods have been tested and developed to infer the presence of Neanderthal or Denisovan AI in humans. Currently, the behaviour of these methods when faced with genomic datasets from evolutionary scenarios other than the human lineage remains unknown. This study therefore focuses on testing the performance of the methods using test data sets simulated under various evolutionary scenarios inspired by the evolutionary history of human, wall lizard (Podarcis) and bear (Ursus) lineages. These lineages were chosen to represent different combinations of divergence and migration times. We study the impact of these parameters, as well as migration rate, population size, selection coefficient and presence of recombination hotspots, on the performance of three methods (VolcanoFinder, Genomatnn and MaLAdapt) and a standalone summary statistic (Q95(w,y)). Furthermore, the hitchhiking effect of an adaptively introgressed mutation can have a strong impact on the flanking regions, and therefore on the discrimination between the genomic windows classes (i.e.AI/non-AI). For this reason, three different types of non-AI windows are taken into account in our analyses: independently simulated neutral introgression windows, windows adjacent to the window under AI, and windows coming from a second neutral chromosome unlinked to the chromosome under AI. Our results highlight the importance of taking into account adjacent windows in the training data in order to correctly identify the window with the mutation under AI. Finally, our tests show that methods based on Q95 seem to be the most efficient for an exploratory study of AI.
B4 Raf-like MAPKKK RAF24 regulatesArabidopsis thalianaflowering time through HISTONE MONO-UBIQUITINATION 2
Authors: Li Qiaomu , Wang Le , Rodriguez Gallo Maria Camila , Mehta Devang , Scandola Sabine , Talasila Mohana , Uhrig RG
Published: June 2024

The timing of flowering is a critical agronomic trait governed by a number of external cues. Despite our genetic understanding of flowering time being well established, we have a limited understanding of how these signals are transmitted to different flowering genes through protein phosphorylation. Here, we characterize a novel B4 Raf-like MAPKKK protein kinase called RAF24, whose mutation results in an early flowering phenotype. Comparative analysis to related B4 Raf-like MAPKKKs indicates that RAF24 unqiuely affects flowering time, while phosphoproteome analyses found RAF24 impacts the phosphorylation status of proteins involved in distinct flowering pathways. In particular, we found the RING-type ubiquitin ligase HISTONE MONO-UBIQUITINATION 2 (HUB2) to possess the largest phosphorylation change inraf24deficient plants relative to wild-type Arabidopsis and that RAF24 suppresses ligase activity of HUB2 in order to maintain approriate levels of H2Bub1. Furthermore, we found that RAF24 regulates HUB2 phosphorylation through subclass I and III SUCROSE NON-FERMENTING KINASE 2 (SnRK2) protein kinases; known substrates of B4 RAF-like MAPKKKs. Lastly, using a combination of phospho-mimetic and -ablative plant lines, we validate the importance of HUB2 phosphorylation at S314in regulating flowering time. Collectively, our findings implicate RAF24 as a higher-order flowering regulator, while further implicating HUB2 as a centerpiece of flowering regulation.
LMNA-Related Dilated Cardiomyopathy: Single-Cell Transcriptomics during Patient-derived iPSC Differentiation Support Cell type and Lineage-specific Dysregulation of Gene Expression and Development for Cardiomyocytes and Epicardium-Derived Cells with Lamin A/C Haploinsufficiency
Authors: Zaragoza Michael V. , Bui Thuy-Anh , Widyastuti Halida P. , Mehrabi Mehrsa , Cang Zixuan , Sha Yutong , Grosberg Anna , Nie Qing
Published: June 2024

LMNA-Related Dilated Cardiomyopathy (DCM) is an autosomal-dominant genetic condition with cardiomyocyte and conduction system dysfunction often resulting in heart failure or sudden death. The condition is caused by mutation in the Lamin A/C (LMNA) gene encoding Type-A nuclear lamin proteins involved in nuclear integrity, epigenetic regulation of gene expression, and differentiation. Molecular mechanisms of disease are not completely understood, and there are no definitive treatments to reverse progression or prevent mortality. We investigated possible mechanisms ofLMNA-Related DCM using induced pluripotent stem cells derived from a family with a heterozygousLMNA c.357-2A>Gsplice-site mutation. We differentiated oneLMNAmutant iPSC line derived from an affected female (Patient) and two non-mutant iPSC lines derived from her unaffected sister (Control) and conducted single-cell RNA sequencing for 12 samples (4 Patient and 8 Control) across seven time points: Day 0, 2, 4, 9, 16, 19, and 30. Our bioinformatics workflow identified 125,554 cells in raw data and 110,521 (88%) high-quality cells in sequentially processed data. Unsupervised clustering, cell annotation, and trajectory inference found complex heterogeneity: ten main cell types; many possible subtypes; and lineage bifurcation for Cardiac Progenitors to Cardiomyocytes (CM) and Epicardium-Derived Cells (EPDC). Data integration and comparative analyses of Patient and Control cells found cell type and lineage differentially expressed genes (DEG) with enrichment to support pathway dysregulation. Top DEG and enriched pathways included: 10ZNFgenes and RNA polymerase II transcription in Pluripotent cells (PP);BMP4and TGF Beta/BMP signaling, sarcomere gene subsets and cardiogenesis,CDH2and EMT in CM;LMNAand epigenetic regulation andDDIT4and mTORC1 signaling in EPDC. Top DEG also included:XISTand other X-linked genes, six imprinted genes:SNRPN,PWAR6,NDN,PEG10,MEG3,MEG8, and enriched gene sets in metabolism, proliferation, and homeostasis. We confirmed Lamin A/C haploinsufficiency by allelic expression and Western blot. Our complex Patient-derived iPSC model for Lamin A/C haploinsufficiency in PP, CM, and EPDC provided support for dysregulation of genes and pathways, many previously associated with Lamin A/C defects, such as epigenetic gene expression, signaling, and differentiation. Our findings support disruption of epigenomic developmental programs as proposed in otherLMNAdisease models. We recognized other factors influencing epigenetics and differentiation; thus, our approach needs improvement to further investigate this mechanism in an iPSC-derived model.
Unveiling the Power of PROTAC Valency: Navigating Cell Type-Specific Hook Effects
Authors: Chitsazan Arash , Eisele Frederik , Rabieifar Parisa , Park Hyunsoo , Nordberg Markus , Liu Jianming , Geschwindner Stefan , Dahl Göran
Published: June 2024

Targeted protein degradation (TPD) using bivalent proteolysis-targeting chimeras (PROTAC) technology has shown potential in expanding the “druggable” proteome. In their publication inNature Chemical Biology, Imaide et al.1posited that augmenting PROTAC valency could potentially lead to the formation of long-lived ternary complexes between PROTAC, the protein of interest (POI), and E3 ligase, thereby constraining the formation of potent binary complexes, as evidenced by a pronounced hook effect. The authors introduced SIM1, a trivalent von Hippel–Lindau (VHL)-based PROTAC, which exhibited a superior degradation profile in comparison to its parent molecule MZ1, towards bromo and extra terminal (BET) proteins, with a predilection for BRD2. The authors attributed this heightened degradation capability of SIM1 over bivalent MZ1 as supportive evidence for their hypothesis. While we concur with the notion that increasing valency and avidity could enhance the efficacy of a PROTAC, the claim that trivalent PROTACs unequivocally eliminate the hook effect is not entirely accurate. We propose that the presence or absence of a hook effect is influenced by numerous factors beyond PROTAC valency.
Flight-Scope: microscopy with microfluidics in microgravity
Authors: Wareing Thomas , Stokes Alexander , Crompton Katrina , Murphy Koren , Dawson Jack , Urgurluoglu Yusuf Furkan , Richardson Connor , Li Hongquan , Prakash Manu , Wollman Adam JM
Published: June 2024

With the European Space Agency (ESA) and NASA working to return humans to the moon and onwards to Mars, it has never been more important to study the impact of altered gravity conditions on biological organisms. These include astronauts but also useful micro-organisms they may bring with them to produce food, medicine, and other useful compounds by synthetic biology. Parabolic flights are one of the most accessible microgravity research platforms but present their own challenges: relatively short periods of altered gravity (~20s) and aircraft vibration. Live-imaging is necessary in these altered-gravity conditions to readout any real-time phenotypes. Here we present Flight-Scope, a new microscopy and microfluidics platform to study dynamic cellular processes during the short, altered gravity periods on parabolic flights. We demonstrated Flight-Scope's capability by performing live and dynamic imaging of fluorescent glucose uptake by yeast, S. cerevisiae, on board an ESA parabolic flight. Flight-Scope operated well in this challenging environment, opening the way for future microgravity experiments on biological organisms.
Mechanotransduction and inflammation: an updated comprehensive representation
Authors: Suryiagandhi Vennila , Ma Ying , Paparozzi Veronica , Guarnieri Tiziana , di Pietro Biagio , Dimitri Giovanna Maria , Tieri Paolo , Sala Claudia , Lai Darong , Nardini Christine
Published: June 2024

Mechanotransduction is the process that enables the conversion of mechanical cues into biochemical signaling. While all our cells are well known to be sensitive to such stimuli, the details of the systemic interaction between mechanical input and inflammation are not always well integrated. Often, they are considered and studied in relatively compartmentalized areas, and we therefore argue here that to understand the relationship of mechanical stimuli with inflammation – with high translational potential - it is crucial to offer and analyze a unified view of mechanotransduction. We therefore offer here a pathway representation, recollected with the standard systems biology markup language (SBML) and explored with network biology approaches. We present RAC1 as an exemplar and emerging molecule with potential for medical translation.
Survey of Chemical Unfolding Complexity as a Unique Stability Assessment Assay for Monoclonal Antibodies
Authors: Floyd J. Alaina , Shaver Jeremy M.
Published: June 2024

Seventy-two intentionally sequence-diverse antibody variable regions were selected, expressed as IgG1 antibodies, and evaluated by chemical unfolding to survey the complexities of denaturant induced unfolding behavior. A two-transition fit well described the curves and uncovered a wide range of sensitivities to denaturant. Four general types of unfolding curves were observed: balanced traces (each transition responsible for half of the total unfolding transition), low-unfolding traces (first transition is a majority of the unfolding curve), high-unfolding traces (the second transition is the majority of the unfolding curve), and coincident traces (the two transitions are found close to each other, approximating a single transition).The complexity of the data from this survey indicates that focusing on the first inflection point or fitting a single transition model is likely an over-simplistic method for measuring stability by the chemical unfolding assay. Additionally, other conformational assays, such as thermal and low pH unfolding, showed no correlation with the chemical unfolding results, indicating that each of these assays provide alternate information on the different pathways of antibody conformational stability. These results provide a basis for beginning to better connect unfolding behavior to other physical phenotypic behaviors and production process behaviors.
Supporting early detection of biological invasions through short-term spatial forecasts of detectability
Authors: Capinha César , Monteiro António T. , Ceia-Hasse Ana
Published: June 2024

Early detection of invasive species is crucial to prevent biological invasions. To increase the success of detection efforts, it is often essential to know the phenological stages in which the invasive species are found. This includes knowing, for example, if invasive insect species are in their adult phase, invasive plants are flowering, or invasive mammals have finished their hibernation. Unfortunately, this kind of information is often unavailable or is provided at very coarse temporal and spatial resolutions. On the other hand, opportunistic records of the location and timing of observations of these stages are increasingly available from biodiversity data repositories. Here, we demonstrate how to apply these data for predicting the timing of phenological stages of invasive species. The predictions are made across Europe, at a daily temporal resolution, including in near real time and for multiple days ahead. We apply this to detectability-relevant phenological stages of four well-known invasive species: the freshwater jellyfish, the geranium bronze butterfly, the floating primrose-willow, and the garden lupine. Our approach uses machine learning and statistical-based algorithms to identify the set of temporal environmental conditions (e.g., temperature values and trends, precipitation, snow depth, and wind speed) associated with the observation of each phenological stage, while accounting for spatial and temporal biases in recording effort. Correlation between predictions from models and the actual timing of observations often exceeded values of 0.9. However, some inter-taxa variation occurred, with models trained on several thousands of observation records performing consistently better than those based on a few hundred records. The analysis of daily predictions also allowed mapping EU-wide regions with similar phenological dynamics (i.e., ‘phenoregions’). Our results underscore the significant potential of opportunistic biodiversity observation data in developing models capable of predicting and forecasting species phenological stages across broad spatial extents. This information has the potential to significantly improve decision-making in invasion surveillance and monitoring activities.