bluuebunny/crossref_metadata_2025 huggingface dataset:
Retrospective analysis of admissions to the emergency department of an urban state hospital: A cross-sectional study of 5,279,630 patient visits (2019–2024)
Authors: Eriten Semih
Published: February 2025

The study aims to comprehensively evaluate the demographic data, diagnostic spectrum, and temporal changes of 5.3 million patients in a state hospital emergency department in an urban area of Istanbul between 2019 and 2024. Data of 5,279,033 patients admitted to Sultanbeyli State Hospital Emergency Department between 2019 and 2024 were retrospectively analyzed. Sociodemographic characteristics, diagnoses, time of presentation, and seasonal variables of 879,839 average annual admissions (minimum: 653,746, maximum: 1068,504) were evaluated. Upper respiratory tract diseases accounted for 26.7% to 35.2% of the admissions during the period analyzed (P < .001). A remarkable increase in the prevalence of myalgia (2019: 5.01%, 2024: 10.29%; odds ratio: 2.17, 95% confidence interval: 1.98–2.37) was observed. In terms of age distribution, while the number of applicants aged 0 to 20 years was 493,382 (48.3%) in 2019, it decreased to 101,560 (15.5%) in 2024 (P < .001). Gender: female predominance was observed in all groups over 21 years of age (odds ratio: 1.43, 95% confidence interval: 1.35–1.52). During the pandemic period (2020–2021), the diagnosis of suspected disease increased to 24.42% and significant changes were observed in emergency department admission dynamics (annual coefficient of variation: 0.68, P < .001). This large-scale epidemiologic study reveals the presentation characteristics of an urban emergency department with an annual average of 880,000 visits. The data, especially the marked variation between age groups and changes in specific diagnostic categories, are of strategic importance for planning health services. Our findings provide an evidence-based basis for the organization of emergency health services in accordance with health needs.
Depression and substance abuse among university students
Authors: Mengistie Kefie Manaye , Berhanu Kelemu Zelalem
Published: February 2025

The purpose of the study was to examine the association between depression and substance abuse and to assess their prevalence and associated factors. A cross-sectional design was employed. To collect data for the present study, 2 scales (Beck depression inventory and Alcohol, Smoking, and Substance Involvement screening Test [ASSIST]) was administered to students. Two hundred fifty seven Addis Ababa Institute of Technology final year regular undergraduate students were participated. The results revealed that a high correlation was found between depression and substance abuse. The prevalence of depression is 27.2%. Similarly, the prevalence of alcohol abuse, khat abuse, cigarette abuse and cannabis abuse are 25.5%, 17.7%, 9.5%, and 3.3% respectively. Hence, the overall substance abuse prevalence is 14%. Alcohol is most abused drug followed by khat abuse. Cigarette and cannabis abuse take the 3rd and 4th rank respectively. Multivariate test of significance reveals that gender, religion and the interaction of gender with religion, residence, and ethnicity had an effect on the two combined dependent measures. Females are more depressed than males. In turn, males are more substance abusers than females. The researchers suggested that the university to establish its own substance abuse prevention and treatment working center which is open for psychologists, therapist and other health workers.
Using smartphone pupillometer application to measure pupil size and light reflex: An unsuccessful prototype and analysis of the causes of failure
Authors: Tan Hung-Hsi , Lee Kuo-Chang , Chen Yi-Rong , Huang Yu-Chin , Ke Rih-Shen , Horng Gwo-Jiun , Chen Kuo-Tai
Published: February 2025

The accurate assessment of pupillary light reflex (PLR) is essential for monitoring critically ill patients, particularly those with traumatic brain injury or stroke and those in postoperative care. Smartphone-based pupillometers represent a potentially cost-effective solution for addressing this need. We developed a smartphone pupillometer application (app) and evaluated its effectiveness against the penlight test and quantitative pupillometry. This study included 50 volunteers aged >20 years and excluded individuals with neurologic or ophthalmic conditions. The app captured pupillary images by displaying a red circle on the screen, and an algorithm processed these images to calculate the pupil constriction percentage (PCP). The results revealed that the smartphone app often required multiple attempts for successful image acquisition. The obtained PCPs were consistently smaller and less variable than those obtained using the penlight test and a commercial pupillometer (app vs penlight for the right eye: 27.0% [27.0%–8.0%] vs 33.0% [32.3%–39.3%]; app vs pupillometer for the right eye: 27.0% [27.0%–28.0%] vs 35.0% [31.8%–38.3%]; app vs penlight for the left eye: 29.0% [28.0%–29.0%] vs 33.0% [29.8%–34.3%]; app vs pupillometer for the left eye: 29.0% [28.0%–29.0%] vs 36.0% [30.8%–38.0%]; P <.001 for all). Notably, the penlight and the pupillometer exhibited comparable PCPs (right eye: penlight vs pupillometer: 33.0% [32.3%–39.3%] vs 35.0% [31.8%–38.3%], P = .469; left eye: penlight vs pupillometer: 33.0% [29.8%–34.3%] vs 36.0% [30.8%–38.0%], P = .148). The app requires further refinement to yield results comparable to those of established methods. Future iterations can include alternative measurement strategies and dynamic assessment. Penlight and quantitative pupillometry remain indispensable as established tools for PLR.
Efficacy of Neoadjuvant Therapy for Resectable Pancreatic Cancer Might be Limited to Biologically Borderline Resectable Cases
Authors: Kato Yoshiyasu , Ashida Ryo , Ohgi Katsuhisa , Otsuka Shimpei , Dei Hideyuki , Uesaka Katsuhiko , Yamazaki Kentaro , Sugiura Teiichi
Published: February 2025

Background:

Neoadjuvant therapy (NAT) followed by surgery is becoming standard treatment even for resectable pancreatic cancer (RPC). However, it is unclear whether NAT is necessary for all RPC cases.

Methods:

296 patients diagnosed with RPC and under 80 years old were retrospectively analyzed, focusing on tumor markers (TM). The cutoff value of TM was decided based on the classification by the International Association of Pancreatology.

Results:

Among 80 cases who underwent NAT, 72 cases were accomplished surgical resection. Upfront surgery (UpS) was planned in 216 cases, and surgical resection was accomplished in 199 cases. Resection rate showed no difference between the two groups (P=0.638). Although NAT group showed a favorable trend in overall survival (OS) compared to the UpS group, the difference was not significant (P=0.143). CA19-9 >500 U/mL and/or DUPAN2 >700 U/mL was defined as high TM. When comparing in TM-high group (n=83), patients with NAT showed significantly better OS than those without NAT (P=0.024). In TM-low group (n=213), the OS curves completely overlapped with no difference (P=0.902). A multivariate analysis demonstrated that undergoing NAT was the sole independent prognostic factor in the TM-high group (Hazard ratio: 0.48, P=0.044), while undergoing NAT was not a prognostic factor in the TM-low group.

Conclusion:

The efficacy of NAT for RPC might be limited to the subset of patients with high TM.
Radiotracer Accumulation in the Pyelocaliceal System of Transplanted Kidney: A Potential Pitfall in Lymphoscintigraphy of Pelvic Malignancies
Authors: Saber Tanha Amin , Elahifard Haniye , Rabani Faeze , Raeisi Nasrin , Sadeghi Ramin
Published: February 2025

A 34-year-old woman with a history of renal transplantation and cervical cancer underwent lymphoscintigraphy using 99mTc-phytate before surgery. Initial planar images revealed multiple foci of uptake, which were later precisely localized using SPECT/CT imaging. Notably, uptakes in the right lower quadrant were attributed to the pyelocalyceal system of the transplanted kidney, highlighting a potential pitfall in patients with ectopic or transplanted kidneys. This case report emphasizes the importance of recognizing the limitations of lymphoscintigraphy in patients with complex anatomy and the value of hybrid imaging in ensuring accurate sentinel lymph node localization.
Mirrored Metastatic Neuroendocrine Tumor in a Mother-Daughter Duo With Mutations in the MEN1 Gene
Authors: Aggarwal Piyush , Kaur Gurjeet , Bhadada Sanjay Kumar , Kumar Rajender , Pandey Somit , Sood Ashwani , Mittal Bhagwant Rai
Published: February 2025

Multiple endocrine neoplasia (MEN) 1 syndrome may present with either of any or all neuroendocrine tumors (NETs), parathyroid and pituitary adenoma. There is a paucity of data on the intronic and exonic mutations in the MEN1 gene associated with the MEN1 syndrome. We present an interesting study of a mother-daughter duo of MEN1 who had a similar lesions distribution of metastatic NET and underwent genetic analysis to reveal a rare mutation in the MEN1 gene and both first-degree relatives presented with metastatic NET without any other syndromic manifestation of MEN1 syndrome. Both patients received peptide receptor radionuclide therapy.
Antrihabitans spumae sp. nov., a novel bacterium isolated from stable foams formed in wastewater treatment plants and emended description of the genus Antrihabitans
Authors: Suescún-Sepúlveda Jhon A. , Riesco Raúl , Petrovski Steve , Soddell Jacques , Sangal Vartul , Jones Amanda L. , Sánchez-Juanes Fernando , Seviour Robert J. , Goodfellow Michael , Trujillo Martha E.
Published: February 2025

Three strains, designated as J27, J71T and J72, belonging to the genus Antrihabitans, were isolated from stable foams formed in activated sludge wastewater treatment plants (WWTPs) in New South Wales, Australia. Phenotypic and genomic analyses revealed that these strains belong to the Nocardiaceae family and are closely related to Antrihabitans stalagmiti. However, distinct genomic and physiological characteristics, including overall genomic relatedness indices, phylogenomic analysis, genomic metabolic profiles and MALDI-TOF MS (Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry), confirmed their status as a new species.

Ecologically, these strains showed a wide metabolic versatility, like enhanced membrane transport systems for amino acids, metals and phosphate, as well as the ability to synthesize mycolic acids, contributing to their hydrophobic nature and involvement in foam stabilization. Their adaptations likely provide a competitive advantage in WWTPs, where they persist in nutrient-rich, metal-laden and foam-stabilizing environments. The species did not present the typical rod-coccus cycle, described previously as a defining characteristic of the Antrihabitans genus. Based on their unique genomic, phenotypic and ecological features, we propose the name Antrihabitans spumae sp. nov., with strain J71T (JCM 34493T, NCIMB 15450T) designated as the type strain. Additional strains include J27 (JCM 33914, NCIMB 15449) and J72 (NCIMB 15448).
A multi-scale segmentation-free self-supervised AI model to characterize the heterogeneity of the brain tumor microenvironment
Authors: Sterling Sam , Tan Jimin , Le Hortense A , Ban Yi , Share Danielle , Snuderl Matija , Tsirigos Aristotelis
Published: February 2025

Brain tumors affect about 1 million people in the U.S., with aggressive types like glioblastoma having very low survival rates due to complex tumor biology and the protective blood-brain barrier. Current treatments are limited in effectiveness, and our understanding of brain tumor biology remains incomplete. High dimensional multiplexed imaging has enabled us to better understand the tumor microenvironment (TME); however, analyses typically rely on cell segmentation, which is error-prone, may discard useful context outside the cell boundary, and neglects complex tissue-wide features. To address this limitation, we developed a segmentation-free, self-supervised representation learning framework that enables us to train directly on multiplexed images using masked image modeling. We used this approach to analyze 389 imaging mass cytometry images from 185 brain tumor patients. To study tissue-wide features, we first trained our model on 64x64 micron tiles capturing neighborhoods of 10-20 cells, which we termed local tumor microenvironments (LTMEs). To further characterize these LTMEs, we trained our model on 16x16 micron tiles centered on individual cells in our dataset, so that each tile captures a single cell and its surrounding area, which we termed single-cell microenvironments (SCMEs). This multi-scale, self-supervised approach enables a detailed analysis of the heterogeneity within the brain TME, examining single cells in their spatial context. In addition to validating known findings, we identified a novel LTME in GBM patients, composed primarily of tumor cells and a few B and T cells, which strongly correlated with increased survival. By analyzing these B cells with our SCME model, we found they were distinct from other GBM B cells, and higher concentrations of these B cells were linked to improved survival. In conclusion, our study introduces a multi-scale, segmentation-free, self-supervised machine learning model that provides unprecedented insights into brain TMEs, enabling discovery of previously unrecognized cell interactions and spatial features that are predictive of patient survival.
Automated Machine Learning Profiling with MAP-HR for Quantifying Homologous Recombination Foci in Patient Samples
Authors: Ozmen Tugba Yildiran , Rames Matthew James , Zangirolani Gabriel Mesquita , Ozmen Furkan , Mills Gordon Brent
Published: February 2025

Accurate visualization and quantification of homologous recombination (HR)-associated foci in readily available patient samples are critical for identifying patients with HR deficiency (HRD) when they present for care to guide polyADP ribose polymerase (PARP) inhibitors (PARPi) or platinum-based therapies. Immunofluorescence (IF) assays have the potential to accurately visualize DNA repair processes as punctate foci within the nucleus. To ensure precise HRD assessment, we developed MAP-HR, (Machine-learning Assisted Profiling of Homologous Recombination), a scalable machine-learning (ML) analysis platform to enable effective patient triage and therapeutic decision-making. This workflow integrates high-resolution four-channel IF imaging and automated analysis of Geminin (cell cycle states), RAD51 (HR repair), γH2AX foci (double strand breaks) and DAPI (nuclear localization) in both cultured cell lines and in a single formalin-fixed, paraffin-embedded (FFPE) patient sample. Using a spinning disk confocal microscope, we optimized imaging parameters to improve resolution and signal-to-noise ratio. Our MAP-HR pipeline uses nested nuclei and segmentation of foci to analyze the HR status of each cell, unlike competing bulk or single-foci marker assays, allowing evaluation of HR functional heterogeneity across and within patient biopsies. This approach facilitates robust comparisons of HR and foci-based processes across diverse cell populations and patient tissues, enabling scalable, translational research.
Isolation of individual natural killer cells from deep, high-aspect ratio microwell arrays - an evaluative study
Authors: Verron Quentin , Sandstrom Niklas , van Ooijen Hanna , Guldevall Karolin , Olofsson Karl , Frisk Thomas , Onfelt Bjorn
Published: February 2025

Immune cells exhibit functional heterogeneity beyond what is resolved by classical definitions of subpopulations based on cell surface expression of receptors. To develop efficient and personalized cell-based immunotherapies, we need to resolve this heterogeneity and understand the underlying parameters that dictate cellular responses to specific target cells. For this, new methods are required that can identify and harvest immune cells with specific functions, e.g., high cytotoxic potential, to form clonally expanded cells or to assess molecular or genetic signatures. In this study, we evaluate a system for non-destructive, live cell picking and release in deep, high-aspect ratio microwells and test it for isolation of individual natural killer (NK) cells. We assess its performance at retrieving and releasing beads from microwells and demonstrate its potential for single NK cell isolation with intact viability. We also implement a semi-automated workflow for functional single-cell screening of NK cell behavior in microwell arrays followed by single-cell identification and isolation, demonstrating the potential for functional screening and isolation of serial killing immune cells. Our evaluation concludes that this cell isolation system, in combination with microwell arrays, offers opportunities for improved understanding of NK cell biology with applications towards cell therapy. However, its limited throughput hinders large-scale applicability.
Autocrine CXCL1-CXCR2 Signaling Mediates Leptomeningeal Resistance to Radiation Therapy
Authors: Osman Ahmed , Remsik Jan , Snyder Jenna , Wijetunga N Ari , Manoranjan Branavan , Nobre Ana Rita , Freret Morgan , Guber David , Chabot Kiana , Peidrafita-Ortiz Sofia , Tong Xinran , Wang Helen , Li Min Jun , Dunbar Andrew Jun , Levine Ross L , Yang Jonathan T , Boire Adrienne
Published: February 2025

Leptomeningeal metastasis (LM) is a fatal neurological complication of cancer. Proton craniospinal irradiation (pCSI) has emerged as a promising life-prolonging intervention for LM patients, but the response to this treatment varies. Here, we aimed to characterize the molecular basis of pCSI resistance and response. Proteomic analysis of CSF collected from LM patients at baseline (before pCSI), and at multiple time points post-treatment, identified the CXC-motif chemokine, CXCL1, as associated with LM growth. Higher CXCL1 levels in the CSF prior to pCSI correlated with worse response to this treatment. To define the role of CXCL1 in LM, we established syngeneic mouse models of LM-CSI. We found that both metastatic cancer and host cells generate CXCL1. Genetic interruption of Cxcl1 expression in metastatic cancer, but not host cells, impaired cancer cell growth within the leptomeninges. Moreover, a subset of LM cancer cells expressed Cxcr2, the primary receptor for Cxcl1, and this population was enriched over time in the leptomeninges. Transcriptomic profiling of this rare population revealed an enrichment in pathways implicated in cell cycle progression. Finally, interruption of Cxcl1-Cxcr2 signaling with intrathecally-delivered Cxcr2 antagonist hampered LM growth and sensitized the cells to CSI. Our results demonstrate that the Cxcl1-Cxcr2 signaling axis mediates LM growth, and identifies a potential actionable intervention to improve response to pCSI and halt LM progression.
Molecular Detection of Human Metapneumovirus in Lagos, Nigeria
Authors: Anjorin Abdul-Azeez Adeyemi , Olaleye Haminat Oluwatoyosi , Sayid Saburi Adekilekun , Ajose Tomisin Deborah , Daniel Grace Treasure , Akinyemi Kabir Olusegun
Published: February 2025

Background: Human metapneumovirus (HMPV) is an important respiratory pathogen worldwide. It is a leading cause of lower respiratory infection in infants, children, elderly and immunocompromised individuals. Methods: This cross-sectional molecular epidemiological study examined HMPV among people with underlying conditions in different clinics in Lagos. Nasopharyngeal samples collected from 150 patients aged 1-88 years between May and June, 2022 were tested by Real-Time Polymerase Chain Reaction. Samples were extracted using Addbio extraction kit (Germany) while master-mix was prepared with primer designed targeting the F protein gene. Results: A total of 15.3% (23/150) was positive for HMPV. The highest HMPV molecular prevalence of 34.8% (8/23) was recorded among the age group (>55 years) while the lowest prevalence of 4.3% (1/23) was recorded in the age group (12-22 years). Male predominance of 56.6% (13/23) was chronicled. Interestingly, HMPV molecular prevalence of 43.3% (10/23), 26.1% (6/23), 21.7% (5/23), 17.4%, (4/23), 13.3% (3/23) were found with co-infection/co-morbidity in malaria, high blood pressure, diabetes, tuberculosis, and pneumonia respectively. Based on location, the highest molecular prevalence was recorded in Badagry 39.1% (9/23), followed by Ojo 34.8% (8/23), while Alimosho recorded the lowest prevalence of 26.1% (6/23). Traders had the highest 39.1% (9/23) molecular prevalence while the lowest 4.3% (1/23) was recorded among patients that are civil servants, musicians, teachers and the unemployed. Conclusion: The interaction between HMPV and other pathogens, such as malaria and respiratory viruses suggests that HMPV may exacerbate existing health conditions or that individuals with these conditions are more prone to HMPV infection. This highlights the need for comprehensive diagnostic approaches in clinical settings to identify and manage multiple infections effectively. The findings accentuates the importance of epidemiological surveillance especially among individuals having underlying diseases and protracted illnesses.
Mavacamten improves energy balance in a pre-clinical model of RASopathy-associated hypertrophic cardiomyopathy
Authors: Ruiz-Velasco Andrea , Jouve Charlène , Deshayes Lucille , Kohlhaas Michael , Maack Christoph , Hulot Jean-Sébastien
Published: February 2025

Background and aim Developmental disorders caused by activating mutations in the RAS-MAPK pathway account for nearly 20% of hypertrophic cardiomyopathy (HCM) cases in paediatric patients. Compared to sarcomeric HCM, RAS-HCM presents a higher risk of obstruction and hospitalisation. The myosin inhibitor mavacamten has been approved in the European Union for treating adults with obstructive HCM; however, clinical trials have excluded syndromic HCM. Consequently, this study aimed to characterise the functional and energetic disturbances induced by the RASopathy mutation BRAF p.Thr599Arg in cardiomyocytes and to evaluate the effects of mavacamten treatment. Methods Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) with a CRISPR-induced BRAF T599R mutation and their isogenic control were employed to model RAS-HCM in vitro. The cell size, contractility, and transcriptomic profile were assessed to determine the phenotype of the cardiomyocytes. Energetics were evaluated using the Mito Stress assay, live ATP levels, and NAD(P)H and FAD+ autofluorescence. Results BRAF-mutant cardiomyocytes demonstrated hypertrophy and hypercontractility. Furthermore, energetic profiling revealed increased mitochondrial NAD(P)H and FAD+ pools and an enhanced energetic state in the Mito Stress assay with increased maximal respiratory capacity. However, they also exhibited a significant ATP drop during rapid pacing compared to the control, suggesting that mitochondrial capacity remains insufficient to meet the ATP demand. Mavacamten treatment normalised excessive ATP consumption during acute pacing, suggesting reduced mitochondrial overactivity. Conclusions BRAF-mutant cardiomyocytes recapitulate the characteristics of HCM in vitro. Mavacamten mmitigates dysfunctions and restores energetic balance under stress conditions, indicating it holds potential as a therapeutic option for RASopathy-associated HCM.
CCRL2 promotes the interferon-γ signaling response in myeloid neoplasms with erythroid differentiation and mutated TP53
Authors: Naji Nour Sabiha , Pasca Sergiu , Chatzilygeroudi Theodora , Toledano-Sanz Pablo , Rimando Joseph , Hemani Yashvi , Perkins Brandy , Zeng Xinghan , Talbot Conover , Paun Bogdan , Abdulmalik Abdulmuez , Lossos Chen , Boronina Tatianna R , Sinanidis Ilias , Tsakiroglou Panagiotis , Fernandes Priyanka , Esteb Christopher , Ambinder Alexander J. , Cole Robert N. , Xian Rena , Gojo Ivana , Paul Suman , Levis Mark J. , DeZern Amy E. , Luznik Leo , Karanika Styliani , Resar Linda S. , Jones Richard J. , Bunz Frederick , Gondek Lukasz , Arvanitis Marios , Karantanos Theodoros
Published: February 2025

Patients with myeloid neoplasms with loss-of-function TP53 mutations and erythroid differentiation have poor outcomes, and a better understanding of disease biology is required. Upregulation of interferon-γ (IFN-γ) signaling has been associated with acute myeloid leukemia (AML) progression and treatment resistance, but its drivers remain unclear. In this study, we found that the surface receptor C-C motif chemokine receptor-like 2 (CCRL2) is overexpressed in AML with erythroid differentiation and TP53 mutations compared to other AML subtypes and healthy hematopoietic cells and its knockout (KO) suppresses erythroleukemia growth in vitro and in vivo. Our proteomics and transcriptomics analysis revealed IFN-γ signaling response as the top CCRL2-regulated pathway in erythroleukemia. Our mechanistic studies support that CCRL2 promotes IFN-γ signaling independent of exogenous IFN-γ, and it induces the phosphorylation of STAT1, the primary regulator of this signaling via JAK2-dependent and independent mechanisms. CCRL2/IFN-γ signaling is upregulated in erythroid leukemias, and TP53 mutated AML without concurrent increase of IFN-γ secretion in the bone marrow microenvironment and is directly induced by TP53 KO. Finally, CCRL2/IFN-γ signaling is associated with the transformation of pre-leukemic single-hit TP53 clones to multi-hit TP53 mutated AML, increased resistance to venetoclax and worse survival in AML. Overall, our findings support that CCRL2 is an essential driver of cell-autonomous IFN-γ signaling response in myeloid neoplasms with erythroid differentiation and TP53 mutations and highlight this signaling as a possible new target for these neoplasms.
Replacing fish meal with untreated and enzymatically treated torula yeast (Cyberlindnera jadinii) affects pelleting die flow resistance and physical properties of the feed pellets
Authors: Miladinovic Dejan Dragan , Salas-Bringas Carlos , Lekang Odd Ivar , Mbuto Esther Julius , Suwal Pashupati
Published: February 2025

Yeast, particularly Cyberlindnera jadinii, is emerging as a significant alternative to fishmeal in aquaculture feed. Fishmeal is known for its superior feed conversion ratios (FCR), but yeast offers promising benefits. This study explores the effects of replacing fishmeal with torula yeast, both untreated and treated with protease and endo-exo 1.3-β-glucanase, on feed pellet properties. Experiment 1 focused on how replacing fishmeal with yeast affects flow resistance and pellet quality. Experiment 2 examined the impact of enzyme-treated yeast on these parameters. The results showed that diets with 20% yeast, whether untreated or enzyme-treated, significantly increased flow resistance during pellet discharge. Additionally, the tensile strength of pellets with 20% yeast improved in both experiments. Pellets containing 10%, 20%, and 100% yeast exhibited aquaphobic behavior, which enhances feed consumption, reduces wastage, and supports sustainable feed manufacturing. However, pellets with 10% and 20% enzyme-treated yeast displayed lipophobic behavior, which is less desirable during post-production processes. Enzymatic treatment also reduced underwater swelling of pellets with 10% and 20% yeast, suggesting minimal enzymatic hydrolysis to lower underwater disintegration. Furthermore, the longitudinal surface roughness of pellets decreased with enzyme-treated yeast, with pellets containing 20% treated yeast showing the smoothest surface. This study highlights the potential of torula yeast as a viable fishmeal alternative, with specific benefits and considerations for its use in aquaculture feed.
LRP2 expression in melanoma is associated with a transitory cell state, increased T cell infiltration, and is upregulated by IFNγ signaling
Authors: Rasmussen Martin Q. , Bønnelykke-Behrndtz Marie L. , Merrild Camilla , Tvilling Ida , Christensen Julie N. , Nielsen Morten M. , Georgsen Jeanette B. , Naumann Nina , Gudbergsson Johann M. , Etzerodt Anders , Pedersen Jakob S. , Jenkins Russell W. , Degn Søren E , Moestrup Søren K. , Schmidt Henrik , Steiniche Torben , Madsen Mette
Published: February 2025

Low density lipoprotein receptor-related protein 2 (LRP2) is a 600 kilodalton multi-ligand endocytic membrane receptor expressed in several cell types during fetal development, including neuroepithelial cells, and in select absorptive epithelial cells in the adult. In epithelial cancers, LRP2 expression is associated with a differentiated tumor cell state and better prognosis. In previous work, we found that while LRP2 is not expressed in benign naevi, it is frequently acquired in melanoma. However, the molecular drivers of LRP2 expression in melanoma and characteristics of LRP2-expressing melanoma have yet to be described. Here, we show that LRP2 expression is related to a transitory melanoma cell state defined by co-expression of melanocyte lineage and neural crest transcriptional programs. Further, we reveal that melanoma LRP2 expression is increased in T cell-inflamed tumors, and is directly upregulated through interferon-gamma signaling. Correlation of melanoma LRP2 expression with clinicopathological variables demonstrates that LRP2 expression is associated with low Breslow thickness and low clinical stage in primary melanomas. Taken together, the present study describes the characteristics of LRP2-expressing melanoma and reveals interferon-gamma signaling as a novel strong positive regulator of LRP2 expression in melanoma.
Chemical enhancement of DNA repair in aging
Authors: Logarinho Elsa , Macedo Joana , Silva Maria Mendes , Magalhaes Joana Miguel , Sousa-Soares Carlos , Ala Maria Ines , Galhardo Mafalda
Published: February 2025

DNA damage is a central driver of the aging process. We previously found that KIF2C, known to play a role in DNA repair, is repressed in aged cells. Here, we investigated if increased KIF2C activity counteracts DNA damage and its effects on aging phenotypes. We show that a small-molecule agonist of KIF2C enhances DNA repair in two distinct genetic disorders exhibiting DNA damage and accelerated aging, the Hutchinson-Gilford progeria (HGPS) and Down (DS) syndromes. Mechanistically, the KIF2C agonist improves the repair of DNA double-strand breaks by inducing nuclear envelope invaginations poked by cytoplasmic microtubules, which translated into amended epigenetic and transcriptional signatures of HGPS and DS. Moreover, subcutaneous administration of the KIF2C agonist in progeria mice mitigated aging phenotypes, extending their healthspan. Our study discloses a unique geroprotective pharmacological approach targeting DNA damage.
Glycogen Engineering Improves the Starvation Resistance of Mesenchymal stem cells and their Therapeutic Efficacy in Pulmonary Fibrosis
Authors: Xu Yongyue , Rahman Mamatali , Wang Zhaoyan , Zhang Bo , Xie Hanqi , Wang Lei , Xu Haowei , Sun Xiaodan , Cheng Shan , Wu Qiong
Published: February 2025

Mesenchymal stem cells (MSCs) are widely used in regenerative medicine, including the treatment of pulmonary fibrosis. However, implanted MSCs disappear within days, constraining therapeutic efficacy, which is largely attributed to nutrient deprivation. In this study, we established glycogen metabolism engineering strategies in mammalian cells. By expressing a functionally optimized glycogen synthase (GYSmut), MSCs could accumulate large amounts of glycogen rapidly as a reserve substance. Glycogen engineering significantly improved the survival of MSCs during starvation both in vitro and in vivo, enhancing cell viability post-implantation and their therapeutic efficacy in pulmonary fibrosis. Glycogen-engineered MSCs may serve as chassis cells for further applications. Our research highlights the importance of glucose metabolism regulation in cell-based therapy and demonstrates the great potential for the metabolic engineering of MSCs and other therapeutic cells.
Yeast HMGB protein Hmo1 is a multifaceted regulator of DNA damage tolerance
Authors: Huo Jinlong , Wei Anhui , Guo Na , Wang Ruotong , Bi Xin
Published: February 2025

The chromosome architecture protein Hmo1 in Saccharomyces cerevisiae is categorized as an HMGB protein as it consists of two structure-specific DNA binding HMGB motifs. However, it deviates from canonical HMGB proteins that have acidic C-terminal domains (CTDs) by bearing a basic one. Hmo1 plays diverse functions in gene regulation and genome integrity. There is evidence implicating Hmo1 in DNA damage tolerance (DDT) that enables DNA replication to bypass lesions on the template. Hmo1 is believed to direct DNA lesions to the error-free template switching (TS) pathway of DDT and aids in the formation of the key TS intermediate sister chromatid junction (SCJ), but the underlying mechanism(s) has yet to be resolved. In this work, we took genetics and molecular biology approaches to further investigate the role of Hmo1 in DDT. We found extensive functional interactions of Hmo1 with components of the genome integrity network in cellular response to the genotoxin methyl methanesulfonate (MMS), implicating Hmo1 in multiple processes in the execution or regulation of homology-directed DNA repair, replication-coupled chromatin assembly, and cell cycle checkpoint. Notably, our data pointed to a role of Hmo1 in directing SJC to the nuclease-mediated resolution pathway instead of the helicase/topoisomerase mediated dissolution pathway for processing/removal. They also suggested that Hmo1 modulates both the recycling of parental histones and the deposition of newly synthesized histones at the replication fork to ensure proper chromatin formation on nascent DNA that is important for DDT. We found evidence that Hmo1 antagonizes the function of histone H2A variant H2A.Z (also known as Htz1 in yeast) in DDT. We also found that Hmo1 is required for DNA damage checkpoint signaling induced by MMS as wells as for DNA negative supercoiling as a proxy of chromatin structure. Moreover, we obtained evidence indicating that the CTD of Hmo1 may or may not be required for its function in DDT depending on the genetic background of the host. Taken together, our findings demonstrate that Hmo1 can contribute to, or regulate, multiple processes of DDT via different mechanisms.
Seasonal Phenology ofEmpoasca fabae(Hemiptera: Cicadellidae) in Québec, Canada
Authors: Santos Abraão Almeida , Araújo Fausto Henrique Vieira , Plante Nicolas , da Silva Ricardo Siqueira , Pérez-Lopéz Edel
Published: February 2025

Climate change is reshaping insect population dynamics in North America, notably impacting the migratory pestEmpoasca fabae(Harris) (Hemiptera: Cicadellidae). While its phenology is well studied in the United States, knowledge gaps exist regarding its dynamics in Eastern Canada, one of its northernmost migration areas. Our study integrates degree-day models, CLIMEX ecological niche modeling, and field-collected data from Québec to assessE. fabaeseasonal phenology and monthly climatic suitability. Our results indicate thatE. fabaecompletes one to two generations in Québec, with earlier emergence and higher generational potential in warmer southeastern regions compared to cooler northeastern regions. CLIMEX modeling showed that suitable climatic conditions forE. fabaegrowth begin in April, peak from May to September, and decline by November. First adult captures occurred from late May to early June, with population peaks in June-July and a decrease by September. Observed adult peaks occurred earlier than predicted by degree-day models, suggesting that additional environmental factors, such as wind patterns and host plant availability, influence early-season population dynamics. This study provides a comprehensive understanding ofE. fabaephenology in Québec and highlights the importance of incorporating climatic and ecological modeling to predict future population trends. Further research on diapause onset, late-season persistence, and migration patterns is needed to refine predictive models and inform pest management strategies in Québec. Understanding these factors will be essential in mitigating potential economic impacts amid ongoing climate change.
The impact of epistasis on the genomic prediction of non-assessed and non-overlapping single crosses in multi-environment trials
Authors: Viana Jose Marcelo Soriano , da Silva Jean Paulo Aparecido
Published: February 2025

Because no previous simulation-based study assessed the influence of epistasis on the genomic prediction of untested single crosses (SCs), the objective was to assess the impact of epistasis on the genomic prediction of untested SCs in multi-environment trials (METs), assuming seven types of digenic epistasis. We genotyped two groups of 70 doubled-haploid lines and phenotyped all 4900 SCs in five environments. The average density for SNPs was 0.03 cM. Regarding the distribution of the SCs over environments, we adopted 10 and 30% of tested SCs and 80% of non-overlapping SCs. To assess the efficacy of the genomic prediction we computed coincidence index (CI) and prediction accuracy. The percentage of the genotypic variance due to epistasis ranged from 18 to 48%. The CI ranged from 0.24 to 0.38, under the lower training set, and between 0.30 to 0.50, assuming the higher training set. Fixing complementary epistasis and increasing the ratio epistatic variance/genotypic variance from 18 to 39% led to a decrease in the coincidence index in the range from 6.5 to 22.0%. Accuracy showed a positive correlation with CI. Assuming epistasis but fitting the additive-dominance model led to a decrease in the CI. Epistasis can significantly affect the genomic prediction of SCs in METs, depending on type, proportion of the genotypic variance due to epistasis. The prediction accuracy efficiently expresses the efficacy of genomic prediction of untested SCs. The genomic prediction of untested single crosses in each environment and across environments is very effective, even under a low training set size.
AI-Driven Breeding Enhances Stress Tolerance in High-Elevation Extremophytes: A Proof-of-Concept Study with Cross-Component Validation
Authors: Kaushik Prashant
Published: February 2025

High-elevation extremophytes exhibit unique survival strategies under harsh climatic conditions, making them attractive targets for sustainable agriculture and climate resilience research. In this study, we present a comprehensive proof of concept application that integrates multi-omics data, environmental simulation, and state of the art machine learning techniques to predict and enhance stress tolerance in these resilient species. Our platform combines graph neural networks (GNNs) for modeling gene environment interactions, digital twin simulations for plant growth prediction, quantum-inspired tensor networks for simulation fidelity, and generative adversarial networks (GANs) for proposing novel gene combinations. Using synthetic data emulating real-world conditions, we demonstrate that our platform can accurately predict plant growth and stress tolerance, with the GNN model achieving a Pearson correlation coefficient of 0.82. Furthermore, the GAN proposed gene combinations that improved predicted stress tolerance by up to 15%. Implemented as a modular backend and an interactive frontend, the application provides a scalable, data-driven roadmap to revolutionize plant breeding. Our results highlight the potential of AI-driven methodologies to accelerate extremophyte breeding, offering valuable insights into the interplay of genomic and environmental factors under extreme conditions, while emphasizing the need for future validation with real-world data.
TEMI: Tissue Expansion Mass Spectrometry Imaging
Authors: Zhang Hua , Ding Lang , Hu Amy , Shi Xudong , Huang Penghsuan , Lu Haiyan , Tillberg Paul W. , Wang Meng C. , Li Lingjun
Published: February 2025

The spatial distribution of diverse biomolecules in multicellular organisms is essential for their physiological functions. High-throughput in situ mapping of biomolecules is crucial for both basic and medical research, and requires high scanning speed, spatial resolution, and chemical sensitivity. Here, we developed a Tissue Expansion method compatible with matrix-assisted laser desorption/ionization Mass spectrometry Imaging (TEMI). TEMI reaches single-cell spatial resolution without sacrificing voxel throughput and enables the profiling of hundreds of biomolecules, including lipids, metabolites, peptides (proteins), and N-glycans. Using TEMI, we mapped the spatial distribution of biomolecules across various mammalian tissues and uncovered metabolic heterogeneity in tumors. TEMI can be easily adapted and broadly applied in biological and medical research, to advance spatial multi-omics profiling.
Fast-tracking native mass spectrometry: Skipping over buffer exchange
Authors: Grun Alice Frederike Rosa , Said Fatema-Aqila , Schamoni-Kast Kira , Damjanovic Tomislav , Bosse Jens B , Uetrecht Charlotte
Published: February 2025

Post-translational modifications play an important role in eukaryotic protein structures and their interactions, which often cannot be achieved in bacterial expression systems such as E.coli. However, it often proves to be quite challenging to produce large amounts of pure protein for downstream analysis like native mass spectrometry (nMS). This is due to lower expression rates in eukaryotic expression systems, such as insect or mammalian cells, compared to bacterial expression systems. Moreover, nMS protocols typically include a buffer exchange step that often results in substantial protein loss, especially when the input material is limited. This buffer exchange step is needed because standard lysis and purification buffers contain Tris, phosphate, or HEPES buffer supplemented with sodium chloride. These are not suitable for nMS as they are non-volatile salts that form adducts during electrospray ionization (ESI), resulting in interference with the signal. Here, we developed a novel method that eliminates the buffer exchange step after protein purification to allow nMS measurements by directly eluting the proteins of interest with an ammonium-acetate-based buffer. We show that the presence of common eluents used in affinity purification protocols, such as imidazole, biotin, and desthiobiotin, is compatible with obtaining high-quality spectra to derive protein stoichiometry and even analyzing enzymatic processes.
Staining-free Visualization of Cell Boundaries in Sliced Tissues for Accurate Binning of Gene Expression in Spatial Transcriptomics
Authors: Zhang Zhiming , Chen Xiaoxia , Chen Youyuan , Liao Zixuan , Liu Tzu-Ming
Published: February 2025

Overcoming the limitations of sparse expression data in high-resolution spatial transcriptomics remains a major challenge for dimensionality reduction and clustering analysis. Visualizing or inferring tissue cell boundaries using dye staining on the same slice can help assign capture spots on the chip to corresponding unit cells and enhance UMI counts and the number of detected genes. However, the staining process may disrupt tissue structures or degrade mRNA, leading to inaccurate spot assignment and cell annotation. In this study, we employed LysM-Cre mT/mG transgenic mice for spatial transcriptomic analysis, where cell boundaries were delineated by tdTomato signals, and myeloid cells were labeled with enhanced green fluorescent protein (EGFP). With the aid of these fluorescent markers, UMI counts and the number of detected genes per cell exceeded those obtained through naive binning with a square matrix. This staining-free approach for visualizing cell boundaries and landmark proteins provides a valuable framework for the studies of single-cell spatial transcriptomics.
Selective depletion of cancer cells with extrachromosomal DNA via lentiviral infection
Authors: Yi Eunhee , Gujar Amit , Zhao Dacheng , Suina Kentaro , Jin Xue , Pardon Katharina , Yu Qinghao , Kagermazova Larisa , Boeke Jef D , Henssen Anton G , Verhaak Roel
Published: February 2025

Extrachromosomal DNA (ecDNA), a major focal oncogene amplification mode found across cancer, has recently regained attention as an emerging cancer hallmark, with a pervasive presence across cancers. With technical advancements such as high-coverage sequencing and live-cell genome imaging, we can now investigate behaviors and functions of ecDNAs. However, we still lack an understanding of how to eliminate ecDNA. We observed depletion of cells containing ecDNA during lentiviral but not transposon-based transduction while we sought to investigate the mechanism of ecDNA behavior. This discovery may provide critical information on utilizing a lentiviral system in emerging ecDNA research. Additionally, this observation suggests specific sensitivities for cells with ecDNA.
To pack or not to pack: revisiting protein side-chain packing in the post‐AlphaFold era
Authors: Vangaru Sriniketh , Bhattacharya Debswapna
Published: February 2025

Motivation: Protein side-chain packing (PSCP), the problem of predicting side-chain conformation given a fixed backbone structure, has important implications in modeling of structures and interactions. However, despite the groundbreaking progress in protein structure prediction pioneered by AlphaFold, the existing PSCP methods still rely on experimental inputs, and do not leverage AlphaFold-predicted backbone coordinates to enable PSCP at scale. Results: Here, we perform a large-scale benchmarking of the predictive performance of various PSCP methods on public datasets from multiple rounds of the Critical Assessment of Structure Prediction (CASP) challenges using a diverse set of evaluation metrics. Empirical results demonstrate that the PSCP methods perform well in packing the side-chains with experimental inputs, but they fail to generalize in repacking AlphaFold-generated structures. We additionally explore the effectiveness of leveraging the self-assessment confidence scores from AlphaFold by implementing a backbone confidence-aware integrative approach. While such a protocol often leads to performance improvement by attaining modest yet statistically significant accuracy gains over the AlphaFold baseline, it does not yield consistent and pronounced improvements. Our study highlights the recent advances and remaining challenges in PSCP in the post-AlphaFold era. Availability: The code and raw data are freely available at https://github.com/Bhattacharya-Lab/PackBench.
Optimizing Metagenome Analysis for Early Detection of Colorectal Cancer: Benchmarking Bioinformatics Approaches and Advancing Cross-Cohort Prediction
Authors: Su Xiaoquan , Sun Yangyang , Fan Xiaoqian , Zhao Jin , Wu Shunyao , Wu Zhenming , Zhu Wenjie , Gao Hao , Xing Jieqi
Published: February 2025

Colorectal cancer (CRC) continues to be a major global public health challenge. Extensive research has underscored the critical role of the gut microbiome for predictive diagnostics of CRC. However, the variability in analytical methods and microbial features across previous studies has significantly impacted detection performance, hindering further research and application. In this study, we conducted a systematic analysis of over 2,000 gut metagenomic samples from 15 globally-sampled public and in-house cohorts. By benchmarking 1,080 analytical combinations across multiple analytical steps, we established an optimal bioinformatics workflow for metagenome-based CRC detection. Despite the substantial heterogeneity of gut microbiomes across multiple regions and cohorts, our workflow demonstrated the robust performance, achieving an AUROC of 0.83 by identifying consistent microbial dynamic patterns associated with CRC. However, early-stage prediction of CRC, particularly at the precancerous adenomas (ADA) stage, remains challenging due to the instability of microbial signatures across cohorts. To address this, we developed an instance-based transfer learning strategy, Meta-iTL, which improved ADA detection in a newly recruited cohort, increasing the AUROC from 0.58 to 0.77 using models trained on existing cohorts. This study not only provides a comprehensive bioinformatics guild for metagenomic data processing and modeling, but also advances the development and application of non-invasive approaches for the early screening and prevention of CRC.