bluuebunny/crossref_metadata_2025 huggingface dataset:
Targeting the HIV reservoir: chimeric antigen receptor therapy for HIV cure
Authors: Li Shuang , Wang Hu , Guo Na , Su Bin , Lambotte Olivier , Zhang Tong
Published: November 2023

Although antiretroviral therapy (ART) can reduce the viral load in the plasma to undetectable levels in human immunodeficiency virus (HIV)-infected individuals, ART alone cannot completely eliminate HIV due to its integration into the host cell genome to form viral reservoirs. To achieve a functional cure for HIV infection, numerous preclinical and clinical studies are underway to develop innovative immunotherapies to eliminate HIV reservoirs in the absence of ART. Early studies have tested adoptive T-cell therapies in HIV-infected individuals, but their effectiveness was limited. In recent years, with the technological progress and great success of chimeric antigen receptor (CAR) therapy in the treatment of hematological malignancies, CAR therapy has gradually shown its advantages in the field of HIV infection. Many studies have identified a variety of HIV-specific CAR structures and types of cytolytic effector cells. Therefore, CAR therapy may be beneficial for enhancing HIV immunity, achieving HIV control, and eliminating HIV reservoirs, gradually becoming a promising strategy for achieving a functional HIV cure. In this review, we provide an overview of the design of anti-HIV CAR proteins, the cell types of anti-HIV CAR (including CAR T cells, CAR natural killer cells, and CAR-encoding hematopoietic stem/progenitor cells), the clinical application of CAR therapy in HIV infection, and the prospects and challenges in anti-HIV CAR therapy for maintaining viral suppression and eliminating HIV reservoirs.
Use of Stroke Alert Sticker in the Field Decreases Time to Acute Interventions for Ischemic Stroke Patients
Authors: Davis Nicolle W. , Bailey Meghan , Hester Jeannette M. , Bonnell Gabriel , Khanna Anna , Wilson Christina , Jones Jason , Cowart Michael , Singh Amita
Published: November 2023

BACKGROUND: Stroke is a medical emergency requiring timely intervention to optimize patient outcomes. The only treatments currently Food and Drug Administration approved for acute stroke are intravenous (IV) thrombolytics, which require obtaining specific medical history to be administered safely. This medical history may be overlooked in the prehospital setting or lost during patient handoff between emergency medical services (EMS) personnel and hospital staff, delaying treatment. We evaluated whether utilization of a “stroke alert sticker” by EMS to capture key information in the field would decrease door-to-needle (DTN) time. METHODS: Bright-orange “stroke alert stickers” were disseminated to our local EMS agency to be placed on all suspected stroke patients in the field prompting documentation of key elements needed for timely treatment decisions. The “stroke alert sticker” included time last known well, contact information, presenting symptoms, and relevant medications. We evaluated the impact of the “stroke alert sticker” on acute stroke metrics, including DTN time. RESULTS: The project included 220 consecutive stroke alert patients brought to our comprehensive stroke center by a single EMS agency from May 2021 through February 2022. Twenty-one patients were treated with an IV thrombolytic. Overall “stroke alert sticker” use compliance was 40%; for the subgroup of patients who were given an IV thrombolytic, the “stroke alert sticker” was used 60% of the time. In patients who received an IV thrombolytic, prehospital EMS notification was 100% with “stroke alert sticker” use, compared with 75% without (P = .13). In addition, with “stroke alert sticker” utilization, DTN time was reduced by 20 minutes (31 [11] minutes with sticker vs 51 [21] minutes without, P = .04). CONCLUSION: Utilization of the “stroke alert sticker” significantly improved DTN times compared with patients without the sticker. This evidence supports continued use of the “stroke alert sticker” to improve DTN times and patient outcomes.
Effects of Pain Beliefs on Postoperative Pain and Analgesic Consumption in Spine Surgery Patients
Authors: Kose Gulsah , Şirin Keziban
Published: November 2023

PURPOSE: This study evaluates the impact of pain belief on postoperative pain and analgesic consumption in patients undergoing spine surgery. METHODS: This descriptive and cross-sectional study was conducted on 71 patients undergoing spine surgery, who were admitted to the neurosurgery department of a university hospital between January 2021 and April 2022. Descriptive information form, Pain Beliefs Questionnaire, visual analog scale, pain evaluation form, and verbal category scale were used for data collection. RESULTS: Participant mean age was 53 years, and 40.8% underwent spinal disc surgery. A total of 60.2% of the participants experienced moderate postoperative pain, and severe pain was noted during the second postoperative hour, after rest and coughing, which decreased significantly during consecutive hours. Besides, 70.4% of the participants expressed that the level of pain decreased, 43.7% had pain as they expected, 69.0% had intermittent pain, and 53.5% experienced pain at the surgical site. The mean scores obtained from the Organic and Psychological Beliefs subscales of the Pain Beliefs Questionnaire were 4.25 and 4.21, respectively. There was a statistically significant relationship between the Psychological Beliefs and visual analog scale scores after coughing measured in the postoperative 24th and 36th hours. There was also a significant relationship between organic beliefs and working status. There was no statistically significant relationship between analgesic consumption and pain belief. CONCLUSION: Patients undergoing spine surgery experienced moderate pain and had a relatively high level of pain beliefs. Regular evaluation of pain levels and beliefs is required for effective pain management.
Serum trimethylamine N-oxide levels among coronary artery disease and acute coronary syndrome patients: a systematic review and meta-analysis
Authors: Dean Yomna E. , Rouzan Samah S. , Loayza Pintado Jose J. , Talat Nesreen Elsayed , Mohamed Alaa R. H. , Verma Suman , Anwar Kamdi Zainab , Gir Deepak , Helmy Ahmed , Helmy Zakaria , Afzal Ahson , Mady Tamer , Hazimeh Yusef , Aiash Hani
Published: November 2023

Background and Aim:

Recent studies have linked trimethylamine N-oxide (TMAO) to cardiovascular diseases; our study aimed to analyze the association between coronary artery disease (CAD), acute coronary syndrome (ACS), and TMAO.

Methods:

PubMed, Scopus, Embase, and Web of Science were searched using terms such as ʻCADʼ and ʻTMAOʼ. Only observational controlled studies were included. RevMan software version 5.4 was used for the analysis.

Results:

A significant association was found between the CAD group and increased serum TMAO levels compared with the control group (MD=1.16, 95% CI=0.54–1.78, P=0.0003). This association remained significant among acute coronary syndrome patients (MD=0.98, 95% CI=0.73–1.23, P<0.00001) and was also detected among young and old CAD patients (MD=0.35, 95% CI=0.06–0.64, P=0.02 and MD=1.36, 95% CI=0.71–2.01, P<0.0001, respectively). On further analysis of intestinal metabolites, the authors detected an insignificant association between choline, betaine, carnitine, and CAD. According to our sensitivity analysis, TMAO is an acceptable diagnostic marker for CAD (0.721, SE was 0.0816, 95% CI: 0.561–0.881).

Conclusion:

TMAO is an acceptable diagnostic marker for CAD, with significantly higher levels among these patients regardless of their age. Other metabolites did not show such an association. The role of serum level TMAO in the early diagnosis of CAD should be further explored.
Mixed connective tissue and ovarian cancer: a case report
Authors: Kudsi Maysoun , Khalayli Naram , Hola Leen , Aldeeb Maria , Aziz Aghiad
Published: November 2023

Background:

Mixed connective tissue disease (MCTD) is characterized by high titres of distinct antibodies: U1 ribonucleoprotein with variable clinical features seen in rheumatoid arthritis, systemic lupus erythematosus, scleroderma, polymyositis, and dermatomyositis. Limited case reports revealed the association between MCTD and cancer, like lymphoma, lung cancers, and others.

Case presentation:

A 22-year-old female presented with enlargement of the abdomen and oedema of the lower extremities, gradually started 25 days The patient had been diagnosed to have rheumatoid arthritis. She was treated with 7.5 mg/week MTX for 6 months. Physical examination revealed: pallor, lower limb oedema, with synovitis and deformities of hands. The laboratory tests showed anaemia, elevated levels of creatine phosphokinase ESR, positivity of antinuclear antibody, anti-ds DNA, and antinuclear ribonucleoprotein. Urinary protein excretion was 1625 mg/24 h. Chest X-ray showed bilateral pleural effusion. Echocardiography revealed pericardial effusion Thoracic-abdominal and pelvic tomography showed a heterogeneous mass with a diameter of 5 × 6 cm at the expense of the right ovary. The mass was removed surgically, and a biopsy was taken, and was compatible with ovarian high-grade serous adenocarcinoma. A course of solumedrol 1 g/IV/3 days was applied, and then continue with 60 mg/day oral predlone. Later on discharge, she was taken 25 mg/day predlone, and methotrexate 10 mg.

Conclusions:

Our case showed that the patient had no risk factors for developing ovary cancer. On the contrary, our patient was a young, non-smoker, without any previous treatment before the RA diagnosis was taken, and finally, she had 3 children with full-term pregnancy, and well health. This case highlights the importance of maintaining a high index of suspicion for malignancy in MCTD patients. However, further investigation on the role of the immune system in the development of ovarian cancer in women with autoimmune diseases including MCTD remains necessary.
Exploring the mechanism of Si-Ni-San against depression by UPLC-Q-TOF-MS/MS integrated with network pharmacology: experimental research
Authors: Jia Keke , Li Changyin , Xu Meijuan , Dai Guoliang , Zhou Jinyong , Chen Biqing , Zou Jiandong , Li Jia , Zhang Qingyu , Ju Wenzheng
Published: November 2023

Background:

Depression is becoming an urgent mental health problem. Si-Ni-San has been widely used to treat depression, yet its underlying pharmacological mechanism is poorly understood. Thus, we aim to explore the antidepressant mechanism of Si-Ni-San by chemical analysis and in-silico methods.

Methods:

Compounds in Si-Ni-San were determined by ultra-high performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS). Then, bioactive compounds were obtained from Traditional Chinese Medicines for Systems Pharmacology Database and Analysis Platform and SwissADME, and the potential targets of which were acquired from SwissTargetPrediction. Depression-related targets were collected from GeneCards. The intersection between compound-related targets and depression-related targets were screened out, and the overlapped targets were further performed protein-protein interaction, biological functional and pathway enrichment analysis. Finally, networks of Si-Ni-San against depression were constructed and visualized by Cytoscape.

Results:

One hundred nineteen compounds in Si-Ni-San were determined, of which 24 bioactive compounds were obtained. Then, 137 overlapped targets of Si-Ni-San against depression were collected. AKT1, PIK3R1, PIK3CA, mTOR, MAPK1 and MAPK8 were the key targets. Furthermore, PI3K-Akt signalling pathway, serotonergic synapse, MAPK signalling pathway and neurotrophin signalling pathway were involved in the antidepressant mechanism of Si-Ni-San. It showed that components like sinensetin, hesperetin, liquiritigenin, naringenin, quercetin, albiflorin and paeoniflorin were the mainly key active compounds for the antidepressant effect of Si-Ni-San.

Conclusions:

This study demonstrated the key components, key targets and potential pharmacological mechanisms of Si-Ni-San against depression. These results indicate that Si-Ni-San is a promising therapeutic approach for treatment of depression, and may provide evidence for the research and development of drugs for treating depression.
Description of Microcella humidisoli sp. nov. and Microcella daejeonensis sp. nov., isolated from riverside soil, reclassification of Marinisubtilis pacificus as Microcella pacifica comb. nov., and emended description of the genus Microcella
Authors: Molina Ayala Katya Michelle , Kim Seung Bum
Published: November 2023

Three Gram-positive, aerobic and rod shaped actinobacteria, designated strains MMS21-STM10T, MMS21-STM12T and MMS21-STM26, were isolated from riverside soil and subjected to polyphasic taxonomic analysis. The strains grew optimally at mesophilic temperatures (25–30 °C) and neutral to slightly alkaline pH (7–8), and NaCl was not required for growth. Best growth was observed on nutrient agar or marine agar media. The strains contained diphosphatidylglycerol, phosphatidylglycerol and a series of unidentified phospholipids, glycolipids and aminolipids, and anteiso-C15 : 0 and iso-C16 : 0 as the main fatty acids in common. The genome sizes ranged between 2.65 and 2.78 Mbp, and the DNA G+C contents between 70.4 and 72.3 mol%. Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain MMS21-STM10T showed highest sequence similarity of 98.3 % to

Microcella putealis

CV-2T, and MMS21-STM12T and MMS21-STM26 of 99.2–99.3 % to

Microcella flavibacter

WY83T, respectively. In the whole genome-based comparison using the orthologous average nucleotide identity and digital DNA–DNA hybridization, each of strains MMS21-STM10T and MMS21-STM12T could be separated from other species of

Microcella

. The genome analysis also indicated that both strains contained gene clusters involved in the biosynthesis of alkylresorcinol, microansamycin and carotenoids. The phenotypic characteristics again differentiated the strains from related species, and two new species of

Microcella

, Microcella humidisoli sp. nov. (type strain, MMS21-STM10T=KCTC 49773T=LMG 32522T) and Microcella daejeonensis sp. nov. (type strain, MMS21-STM12T=KCTC 49750T=LMG 32523T) are proposed accordingly. It was also evident that

Marinisubtilis pacificus

KN1116T should be reclassified as a new species of

Microcella

, and Microcella pacifica comb. nov. (type strain, KN1116T=CGMCC 1.17143T=KCTC 49299T) is proposed. In addition, an emended description of

Microcella

is proposed based on this study.
Tumebacillus lacus sp. nov., isolated from lake water
Authors: Zhang Jing , Gao Yi-zhou , Du Zong-Jun , Wang Ming-Yi
Published: November 2023

A Gram-stain-positive, aerobic, rod-shaped, endospore-forming and motile, by means of peritrichous flagella, bacterium, designated DT12T, was isolated from a lake water sample from Datun Lake of Yunnan Province, PR China. The results of phylogenetic analysis based on 16S rRNA gene sequence and the concatenated alignment of 120 ubiquitous single-copy proteins indicated that the novel strain represented a member of the genus

Tumebacillus

. The sole quinone was menaquinone-7 and the cell-wall peptidoglycan was type-A1γ. The major fatty acids (>10 %) of the novel strain were iso-C15 : 0 and anteiso-C15 : 0, while the major polar lipids were phosphatidylmonomethylethanolamine, phosphatidylethanolamine and phosphatidylglycerol. The results of phylogenetic analyses combined with phylogenetic, phenotypic and chemotaxonomic features, strongly supported the hypothesis that the strain should be classified as representing a novel species of the genus

Tumebacillus

, for which the name Tumebacillus lacus sp. nov. is proposed. The type strain is DT12T (=KCTC 33958T= MCCC 1H00320T). The genomic analysis revealed that DT12T has various biosynthetic gene clusters for secondary metabolites, and members of the genus

Tumebacillus

may represent a promising source of new natural products. Our study also showed that members of the genus

Tumebacillus

are widely distributed in a variety of habitats throughout the globe, particularly in soils, human-, animal- and plant-associated environments. Members of the genus

Tumebacillus

may have an important role in the growth and health of humans, plants and animals.
Predictive Modeling of Resistant Hypertension Risk: Incorporating the TyG Index and Clinical Factors
Authors: Yang Hai-Tao , Liu Jing-Kun , Yang YI , Zheng Ying-Ying , Xie Xiang
Published: November 2023

Background

Resistant hypertension (RH), a form of high blood pressure that remains uncontrolled despite maximum medication, poses a significant cardiovascular risk. This paper introduces a novel predictive model, combining the triglyceride-glucose (TyG) index with traditional clinical factors, to anticipate the development of RH in patients with newly diagnosed primary hypertension.

Methods

The study included hospitalized patients with newly diagnosed primary hypertension and stable blood pressure after medication treatment from August 2019 to early August 2021. After screening, a total of 1635 cases were finally included and divided into development and validation cohorts. The least absolute shrinkage and selection operator (LASSO) regression was applied to select potential risk factors. Multivariate Cox regression analysis was used to identify independent hazard factors constructed by the predictive nomogram. Receiver operating characteristic curve analysis (ROC), calibration curve, and C-index were used to evaluate the performance of the nomogram.

Results

A total of 1227 patients were assigned to the development queue, while 408 patients were assigned to the validation queue. The constructed column line chart includes five clinical variables: age, apnea-hypopnea index (AHI), uric acid, fasting blood glucose, and TyG index. Multivariate Cox regression analysis revealed that compared to the other four risk factors, TyG index (HR=3.97, 95% CI: 2.81 - 5.62, P < 0.01) was significantly associated with RH. ROC curve analysis showed prediction values of 0.895 and 0.837 for RH in the development cohort and prediction values of 0.854 and 0.832 in the validation cohort respectively. The C-index was found to be 0.76 in the development cohort and 0.66 in the validation cohort. Furthermore, Kaplan-Meier analysis indicated that compared to the low-risk group, there was a higher likelihood of developing RH in the high-risk group.

Conclusions

Based on the TyG index and electronic health record data, a model can be constructed to accurately and reliably predict the occurrence of RH in patients with stable blood pressure after initial diagnosis of primary hypertension and drug treatment.
DeepGSEA: Explainable Deep Gene Set Enrichment Analysis for Single-cell Transcriptomic Data
Authors: Xiong Guangzhi , LeRoy Nathan John , Bekiranov Stefan , Zhang Aidong
Published: November 2023

Gene set enrichment (GSE) analysis allows for an interpretation of gene expression through pre-defined gene set databases and is a critical step in understanding different phenotypes. With the rapid development of single-cell RNA sequencing (scRNA-seq) technology, GSE analysis can be performed on fine-grained gene expression data to gain a nuanced understanding of phenotypes of interest. However, due to the extreme heterogeneity of single-cell gene expression, current statistical GSE analysis methods sometimes fail to identify enriched gene sets. Meanwhile, deep learning has gained traction in specific applications like clustering and trajectory inference in single-cell studies due to its prowess in capturing complex data patterns. However, its use in GSE analysis remains limited, primarily due to interpretability challenges. In this paper, we present DeepGSEA, an explainable deep gene set enrichment analysis approach which leverages the expressiveness of interpretable, prototype-based neural networks to provide an in-depth analysis of GSE. DeepGSEA learns the ability to capture GSE information through our designed classification tasks, and significance tests can be performed on each gene set, enabling the identification of enriched sets. The underlying distribution of a gene set learned by DeepGSEA can be explicitly visualized using the encoded cell and cellular prototype embeddings. We demonstrate the expressiveness of DeepGSEA over commonly used GSE analysis methods by examining their sensitivity and specificity with four simulation studies. In addition, we test our model on three real scRNA-seq datasets and illustrate the interpretability of DeepGSEA by showing how its results can be explained. The source code of DeepGSEA is available athttps://github.com/Teddy-XiongGZ/DeepGSEA.
Linking the gut microbiome to host DNA methylation by a discovery and replication epigenome-wide association study
Authors: Demirkan Ayşe , van Dongen Jenny , Finnicum Casey T. , Westra Harm-Jan , Jankipersadsing Soesma , Willemsen Gonneke , Ijzerman Richard G. , Boomsma Dorret I. , Ehli Erik A. , Bonder Marc Jan , Fu Jingyuan , Franke Lude , Wijmenga Cisca , de Geus Eco J.C. , Kurilshikov Alexander , Zhernakova Alexandra
Published: November 2023

Both gene methylation and the gut microbiome are partially determined by host genetics and partially by environment. We investigated the relations between gene methylation in blood and the abundance of common gut bacteria profiled by 16s rRNA gene sequencing in two population-based Dutch cohorts: LifeLines-Deep (LLD, n = 616, discovery) and the Netherlands Twin Register (NTR, n = 296, replication). In LLD, we also explored microbiome composition using data generated by shotgun metagenomic sequencing (n = 683). We then investigated if genetic and environmental factors can explain the methylation–microbiota associations in a set of 78 associated CpG–taxa pairs from the EWAS meta-analysis. In both cohorts, blood and stool samples were collected within 2 weeks of each other. Methylation was profiled in blood samples using the Illumina 450K array. Methylation and microbiome analysis pipelines were harmonized across cohorts. Epigenome-wide association study (EWAS) of microbial features were analysed using linear regression with adjustment for technical covariates.

Discovery and replication analysis using 16s data identified two independent CpGs associated with the genusEggerthella: cg16586104 (Pmeta-analysis= 3.21 × 10-11) and cg12234533 (Pmeta-analysis= 4.29 × 10-10). While we did not find human genetic variants that could explain the associated CpG–taxa/pathway pairs, we show that microbiome can mediate the effect of environmental factors on epigenetics.

In this first association study linking epigenome to microbiome, we found and replicated the associations of two CpGs to the abundance of genusEggerthellaand identified microbiome as a mediator of the exposome.
Using large language models to study human memory for meaningful narratives
Authors: Georgiou Antonios , Can Tankut , Katkov Mikhail , Tsodyks Misha
Published: November 2023

One of the most impressive achievements of the AI revolution is the development of large language models that can generate meaningful text and respond to instructions in plain English with no additional training necessary. Here we show that language models can be used as a scientific instrument for studying human memory for meaningful material. We developed a pipeline for designing large scale memory experiments and analyzing the obtained results. We performed online memory experiments with a large number of participants and collected recognition and recall data for narratives of different lengths. We found that both recall and recognition performance scale linearly with narrative length. Furthermore, in order to investigate the role of narrative comprehension in memory, we repeated these experiments using scrambled versions of the presented stories. We found that even though recall performance declined significantly, recognition remained largely unaffected. Interestingly, recalls in this condition seem to follow the original narrative order rather than the scrambled presentation, pointing to a contextual reconstruction of the story in memory.
Transcriptomic Profiling Reveals Claudin 18.2 as a Diagnostic Biomarker of Ménétrier’s Disease and the Role of Hedgehog Signaling in Pathogenesis
Authors: Shin Miyoung , Gabriel Tryston , Coffey Robert J. , Huh Won Jae
Published: November 2023

Both Ménétrier’s disease (MD) and juvenile polyposis syndrome (JPS) are rare premalignant conditions that can lead to gastric cancer development. MD is an acquired disease without known causative mutations. MD patients are characterized by an increased expression of EGF receptor (EGFR) ligand and transforming growth factor alpha (TGF-α) in the stomach. JPS is inherited in an autosomal dominant pattern and is caused byBMPR1AorSMAD4mutations. It is characterized by multiple polyps throughout the gastrointestinal tract along with certainSMAD4mutations that can result in gastric polyposis. Although there are many distinct clinico- endoscopic and histopathologic features that differ between the two diseases, they also share similar features that often lead to misdiagnosis. This study aimed to identify markers that can help distinguish MD from JPS and to better understand the pathogenesis of MD by comparing differential gene expression patterns.

Upon examination of MD and JPS microscopically, we found almost all cases have patchy areas mimicking each other, making it difficult to make a correct diagnosis with histopathologic examination alone. Comparative analysis between MD and JPS using ingenuity pathway analysis (IPA) revealed both common and differential gene signatures. Common gene signatures included estrogen receptor signaling, integrin signaling, mTOR signaling, and others, which may be responsible for histopathologic similarities. Among differential gene signatures, we found thatclaudin 18(CLDN18) is upregulated in MD and confirmed that CLDN18.2 (isoform of CLDN18) protein expression is higher in MD than JPS by immunohistochemistry. Comparative analysis between MD and normal control revealed the hedgehog (Hh) signaling pathway is upregulated in MD. Treatment with a hedgehog pathway inhibitor partially rescued the histopathologic phenotypes in a MD mouse model.

The current study provides valuable insight into the potential underlying mechanism of why MD and JPS show similar clinico-pathologic features. We also identified a diagnostic marker CLDN18.2 that can help distinguish MD from JPS, genetically. Furthermore, it also shows that Hh signaling plays an important role in the pathogenesis of MD and can function as a potential therapeutic target.
Multi-omics characterization of lymphedema-induced adipose tissue from breast cancer patients
Authors: Karaman Sinem , Lehti Satu , Zhang Cheng , Taskinen Marja-Riitta , Käkelä Reijo , Mardinoglu Adil , Brorson Håkan , Alitalo Kari , Kivelä Riikka
Published: November 2023

Objective

Secondary lymphedema (LE) following breast cancer surgery is a life-long complication, which currently has no cure. LE induces significant regional adipose tissue deposition, requiring liposuction as a treatment. Here, we aimed to elucidate the transcriptional, metabolomic, and lipidomic signature of the adipose tissue developed due to the surgery-induced LE in short- and long-term LE patients, and compared the transcriptomic landscape in LE to the obesity-induced adipose tissue.

Methods

Adipose tissue biopsies were obtained from breast cancer-operated females with LE from the affected and non-affected arms (n=20 patients). To decipher molecular properties of the LE adipose tissue, we performed RNA sequencing, metabolomics, and lipidomics combined with bioinformatics analyses.

Results

Integrative analysis of functional genomics revealed that inflammatory response, cell chemotaxis and angiogenesis were upregulated biological processes in the LE arm, indicating a sustained inflammation in the edematous adipose tissue, whereas, epidermal differentiation, cell-cell junction organization, water homeostasis and neurogenesis were, in turn, downregulated in the LE arm. Surprisingly, only few genes were found to be the same in the LE-induced and the obesity-induced adipose tissue expansion, indicating a different type of adipose tissue development in these two diseases. In metabolomics analysis, the concentration of a branched-chain amino acid valine was found to be reduced in the edematous arm together with downregulation of mRNA levels of its transporterSLC6A15. Lipidomics analyses did not show any significant differences between the diseased and healthy arm, suggesting that diet affects the lipid composition of the adipose tissue more than the LE.

Conclusions

Our results provide a detailed molecular characterization of adipose tissue in secondary LE of breast cancer patients vs individuals with obesity. The results show distinct differences in transcriptomic signatures between LE patients vs individuals with obesity, but only minor differences in metabolome and lipidome between the diseased and the healthy arm.
MIOSTONE: Modeling microbiome-trait associations with taxonomy-adaptive neural networks
Authors: Jiang Yifan , Atton Matthew , Zhu Qiyun , Lu Yang
Published: November 2023

The human microbiome, a complex ecosystem of microorganisms inhabiting the body, plays a critical role in human health. Investigating its association with host traits is essential for understanding its impact on various diseases. Although shotgun metagenomic sequencing technologies have produced vast amounts of microbiome data, analyzing such data is highly challenging due to its sparsity, noisiness, and high feature dimensionality. Here we develop MIOSTONE, an accurate and interpretable neural network model that simulates a real taxonomy by encoding the relationships among microbial features. The taxonomy-encoding architecture provides a natural bridge from variations in microbial taxa abundance to variations in traits, encompassing increasingly coarse scales from species to domains. MIOSTONE has the ability to determine whether taxa within the corresponding taxonomic group provide a better explanation in a data-driven manner. MIOSTONE serves as an effective predictive model, as it not only accurately predicts microbiome-trait associations across extensive real datasets but also offers interpretability for scientific discovery. Both attributes are crucial for facilitating in silico investigations into the biological mechanisms underlying such associations among microbial taxa.
Convolutional neural network model detected lasting behavioral changes in mouse with kanamycin-induced unilateral inner ear dysfunction
Authors: Noda Masao , Mari Shimada Dias , Sajjaviriya Chortip , Koshu Ryota , Saito Chizu , Ito Makoto , Koshimizu Taka-aki
Published: November 2023

In acute aminoglycoside ototoxicity to unilateral inner ear, physical abnormalities, such as nystagmus and postural alteration, are relieved within a few days by neural compensation. To examine exploratory behavior over an extended period, freely moving behavior of a mouse after unilateral kanamycin injection was recorded in a home-cage environment. A tail was excluded from deep learning-mediated object detection because of its delayed movement relative to the body. All detection results were confirmed by convolutional neural network classification model. In kanamycininjected mice, total distance moved in 15 minutes increased at 3 days after surgery. Moreover, the injured mouse turned frequently toward healthy side up to 17 days after surgery. Tail suspension and twist toward healthy side induced fast rotation of trunk around longitudinal axis with dorsal bending after 14 days. Our analysis strategy employing deep learning is useful to evaluate neuronal compensatory process and screen a drug candidate with therapeutic potency.
Movi: a fast and cache-efficient full-text pangenome index
Authors: Zakeri Mohsen , Brown Nathaniel K. , Ahmed Omar Y. , Gagie Travis , Langmead Ben
Published: November 2023

Efficient pangenome indexes are promising tools for many applications, including rapid classification of nanopore sequencing reads. Recently, a compressed-index data structure called the “move structure” was proposed as an alternative to other BWT-based indexes like the FM index and r-index. The move structure uniquely achieves both O(r) space and O(1)-time queries, where r is the number of runs in the pangenome BWT. We implemented Movi, an efficient tool for building and querying move-structure pangenome indexes. While the size of the Movi’s index is larger than the r-index, it scales at a smaller rate for pangenome references, as its size is exactly proportional to r, the number of runs in the BWT of the reference. Movi can compute sophisticated matching queries needed for classification – such as pseudo-matching lengths and backward search – at least ten times faster than the fastest available methods, and in some cases more than 30-fold faster. Movi achieves this speed by leveraging the move structure’s strong locality of reference, incurring close to the minimum possible number of cache misses for queries against large pangenomes. We achieve still further speed improvements by using memory prefetching to attain a degree of latency hiding that would be difficult with other index structures like the r-index. Movi’s fast constant-time query loop makes it well suited to real-time applications like adaptive sampling for nanopore sequencing, where decisions must be made in a small and predictable time interval.
Exploring building blocks of cell organization by estimating network motifs using graph isomorphism network
Authors: Yu Yang , Wang Shuang , Xu Dong , Wang Juexin
Published: November 2023

The spatial arrangement of cells within tissues plays a pivotal role in shaping tissue functions. A critical spatial pattern is network motif as the building blocks of cell organization. Network motifs can be represented as recurring significant interconnections of cells with various types in a spatial cell-relation graph, i.e., enriched occurrences of isomorphic subgraphs in the graph, which is computationally infeasible to have an optimal solution with large-size (>3 nodes) subgraphs. We introduceTriangulation NetworkMotifNeuralNetwork (TrimNN), a neural network-based approach designed to estimate the prevalence of network motifs of any size in a triangulated cell graph. TrimNN simplifies the intricate task of occurrence regression by decomposing it into several binary present/absent predictions on small graphs. TrimNN is trained using representative pairs of predefined subgraphs and triangulated cell graphs to estimate overrepresented network motifs. On typical spatial omics samples within thousands of cells in dozens of cell types, TrimNN robustly infers the presence of a large-size network motif in seconds. In a case study using STARmap Plus technologies, TrimNN identified several biological meaningful large-size network motifs significantly enriched in a mouse model of Alzheimer’s disease at different months of age. TrimNN provides an accurate, efficient, and robust approach for quantifying network motifs, which helps pave the way to disclose the biological mechanisms underlying cell organization in multicellular differentiation, development, and disease progression.
Analyzing asymmetry in brain hierarchies with a linear state-space model of resting-state fMRI data
Authors: Benozzo Danilo , Baggio Giacomo , Baron Giorgia , Chiuso Alessandro , Zampieri Sandro , Bertoldo Alessandra
Published: November 2023

The study of functional brain connectivity in resting-state functional magnetic resonance imaging (rsfMRI) data has traditionally focused on zero-lag statistics. However, recent research has emphasized the need to account for dynamic aspects due to the complex patterns of time-varying co-activations among brain regions. In this regard, the importance of non-zero-lag statistics in studying complex brain interactions has been emphasized, both in terms of modeling and data analysis. Here, we show how a time-lag description is incorporated within the framework of dynamic causal modeling (DCM) resulting in an asymmetric state interaction matrix known as effective connectivity (EC). Asymmetry in EC is conventionally associated with the directionality of interactions between brain regions and is frequently employed to distinguish between incoming and outgoing node connections. We will revisit this interpretation by employing a decomposition of the EC matrix. This decomposition enables us to isolate the steady-state differential crosscovariance matrix, which is responsible for modeling the information flow and introducing time irreversibility. In other words, by modeling the off-diagonal part of the differential covariance, the system landscape may exhibit a curl steady-state flow component that breaks detailed balance and diverges the dynamics from equilibrium. Our empirical results reveal that only the outgoing strengths of the EC matrix relate with the flow described by the differential cross-covariance, while the so-called incoming strengths are primarily driven by the zero-lag covariance, specifically the precision matrix, thus reflecting conditional independence rather than directionality.
Ultra-Long-Term Delivery of Hydrophilic Drugs Using InjectableIn SituCross-Linked Depots
Authors: Lee Sohyung , Zhao Spencer , Jiang Weihua , Chen Xinyang , Zhu Lingyun , Joseph John , Agus Eli , Mary Helna Baby , Barooj Shumaim , Slaughter Kai , Cheung Krisco , Luo James N , Shukla Chetan , Gao Jingjing , Lee Dongtak , Balakrishnan Biji , Jiang Christopher , Gorantla Amogh , Woo Sukyung , Karp Jeffrey M , Joshi Nitin
Published: November 2023

Achieving ultra-long-term release of hydrophilic drugs over several months remains a significant challenge for existing long-acting injectables (LAIs). Existing platforms, such asin situforming implants (ISFI), exhibit high burst release due to solvent efflux and microsphere-based approaches lead to rapid drug diffusion due to significant water exchange and large pores. Addressing these challenges, we have developed an injectable platform that, for the first time, achieves ultra-long-term release of hydrophilic drugs for over six months. This system employs a methacrylated ultra-low molecular weight pre-polymer (polycaprolactone) to createin situcross-linked depots (ISCD). The ISCD’s solvent-free design and dense mesh network, both attributed to the ultra-low molecular weight of the pre-polymer, effectively minimizes burst release and water influx/efflux.In vivostudies in rats demonstrate that ISCD outperforms ISFI by achieving lower burst release and prolonged drug release. We demonstrated the versatility of ISCD by showcasing ultra-long-term delivery of several hydrophilic drugs, including antiretrovirals (tenofovir alafenamide, emtricitabine, abacavir, and lamivudine), antibiotics (vancomycin and amoxicillin) and an opioid antagonist naltrexone. Additionally, ISCD achieved ultra-long-term release of the hydrophobic drug tacrolimus and enabled co-delivery of hydrophilic drug combinations encapsulated in a single depot. We also identified design parameters to tailor the polymer network, tuning drug release kinetics and ISCD degradation. Pharmacokinetic modeling predicted over six months of drug release in humans, significantly surpassing the one-month standard achievable for hydrophilic drugs with existing LAIs. The platform’s biodegradability, retrievability, and biocompatibility further underscore its potential for improving treatment adherence in chronic conditions.
A new cloud forest treeLychnodiscus bali(Sapindaceae), Critically Endangered from the Bali-Ngemba Forest reserve, N.W. Region, Cameroon
Authors: Cheek Martin , Onana Jean Michel , Lachenaud Olivier
Published: November 2023

We describeLychnodiscus bali(Sapindaceae) a new species to science, from the Bali Ngemba Forest Reserve of NW Region Cameroon, the last major remnant of cloud forest in the Bamenda Highlands of Cameroon, recently evidenced as a Tropical Important Plant Area (TIPA or IPA). Confined on current evidence to upper submontane forest, the species is threatened by expanding habitat clearance for farms and is assessed as Critically Endangered. A small tree, attaining 3–4 m height, it is the first new species to be added to this Guineo-Congolian tree genus in 50 years, the third recorded from Cameroon, and takes the number of species in the genus to eight. It has the highest known altitudinal range (1700 – 1950 m alt.), of any species of the genus.

Previously identified asLychnodiscus grandifolius, the new species differs in the shorter length of the distal leaflets (12 – 18 cm vs 22 – 39 cm long), in the abaxial surface lacking glands (vs glands flat and conspicuous), tertiary nerves hairy (vs glabrous), flowers at anthesis 8 – 11 mm long (vs 5 – 7 mm long).

Lychnodiscus baliis described, illustrated and its extinction risk assessment as Critically Endangered is presented. We discuss its discovery in the context of other recently discovered and highly threatened or even extinct plant species in the Cameroon Highlands, and the importance of their conservation.

We present an updated key to the identification of the species of the genus,and discuss its classification in the context of recent molecular phylogenomic studies. Previously placed in Cupanieae by Radlkofer, the authors contend thatLychnodiscusshould now be placed in the reconstituted Nepheliaeae in the revised 2021 intrafamilial classification of Buerki et al., probably close to the generaAporrhizaandLaccodiscus. However, until the genus is included in molecular studies this cannot be confirmed and its sister relationship remains speculative.
Renal mechanotransduction is an essential regulator of renin
Authors: Hill Rose Z. , Shirvan Sepenta , Burquez Sebastian , Dubin Adrienne E. , Servin-Vences M. Rocio , Miner Jeffrey H. , Patapoutian Ardem
Published: November 2023

The kidneys tightly control the composition of our internal environment to maintain homeostasis in the face of external variability. The regulation of blood volume begins in the kidneys and is essential for vertebrate life in terrestrial environments where salt and water availability are unpredictable1,2. Renin synthesis and release by juxtaglomerular granular cells of the kidney is the rate-limiting step in a hormonal cascade that modulates blood volume, filtration, and salt balance2. Renin is stimulated during hypovolemia and salt deprivation in response to chemical cues released from sympathetic efferent neurons and the macula densa onto the juxtaglomerular granular cells. Renin levels are also proposed to be modulated by mechanical forces elicited by changes in blood volume and/or pressure exerted upon juxtaglomerular cells2–4. However, the identity and significance of the juxtaglomerular mechanotransducer(s) was unknown. We found that the force-gated ion channel PIEZO2 is expressed in juxtaglomerular granular cells and in neighboring mesangial cells. Selective genetic ablation of PIEZO2 dysregulated the renin-angiotensin-aldosterone system by elevating renin, raising systemic blood pressure, inducing glomerular hyperfiltration, and exaggerating the hormonal response to volume depletion. These findings demonstrate that PIEZO2 contributes to renal blood volume sensing and kidney functionin vivo.
Validation and Responsiveness of the English version of the Chemotherapy-Induced Alopecia Distress Scale (CADS) in Breast Cancer Patients
Authors: Kraehenbuehl L. , Kang D. , Bang A. S. , Ketosugbo K. F. , Hay J. , Patil Sujata , Goldfarb S. , Cho J. , Lacouture M. E.
Published: November 2023

Purpose

This study aimed to validate the chemotherapy-induced alopecia distress scale (CADS) in a diverse English-speaking population and patients with endocrine treatment- induced alopecia (EIA).

Objective

Chemotherapy and endocrine therapy commonly cause alopecia in breast cancer patients, leading to significant psychological and social challenges. The CADS was developed to assess the psychosocial impact of alopecia, but its generalizability beyond Korean patients requires further investigation.

Methods

Data from the CHANCE study (NCT02530177), which focused on non-metastatic breast cancer, was used. The cohort included 256 patients, and CADS data were collected at baseline, six months after chemotherapy completion, or 12 months after initiating endocrine therapy. The CADS questionnaire comprised 17 items covering physical and emotional health, daily activities, and relationships. Reliability was assessed using Cronbach’s alpha, and responsiveness was measured by effect size.

Results

The CADS exhibited good reliability, with a Cronbach’s alpha of 0.91 for the overall score, indicating acceptable internal consistency in both chemotherapy (0.89) and endocrine therapy (0.86) groups. Longitudinal responsiveness was supported by an effect size of 0.49 between decreasing satisfaction with hair growth and increasing emotional distress. Cross-sectional validity was confirmed, with effect sizes of 0.91 and 0.92 for satisfaction with hair growth and emotional and activity domains, respectively.

Conclusion

The CADS is a valid and responsive tool for assessing the psychosocial impact of chemotherapy-induced alopecia and endocrine treatment-induced alopecia in a diverse Western patient population.
National diagnostic reference levels for digital diagnostic and screening mammography in Uganda
Authors: Odongo Denish , Musisi Alen , Okello Richard Omara , Bongomin Felix , Erem Geoffrey
Published: November 2023

Introduction

Screening and diagnostic mammography are associated with some risk of radiation-induced breast cancer. This study was conducted to establish the National Diagnostic Reference Levels (NDRLs) for digital diagnostic and screening mammography in Uganda to achieve breast radiation dose optimization.

Methods

A cross-sectional study was conducted among female participants recruited by a consecutive sampling from three selected Hospitals with digital mammography in Uganda. The study variables extracted from the mammography machines were exposure factors, compressed breast thickness (CBT), and Average Glandular Dose (AGD) of two standard mammogram views. The stratified National DRL was derived by calculating 75thpercentile of the AGD across all the samples at various CBT ranges for both screening and diagnostic mammography in craniocaudal (CC) and mediolateral oblique (MLO) views.

Results

We included 300 participants with mean ages of 50.28±9.32 and 47.45±13.45 years for the screening and diagnostic mammography, respectively. There were statistically significant positive correlations between AGD and exposures factors (mAs, kVp) (all p-values<0.0001). For screening mammography, mAs demonstrated a strong positive correlation (r = 0.8369 in CC, 0.8133 in MLO), whereas kVp showed positive correlation with relatively lower coefficients (r = 0.3700 in CC, 0.3080 in MLO). In diagnostic mammography, mAs exhibited an even stronger positive correlation (r = 0.8987 in CC, 0.8762 in MLO), and kVp maintained a positive correlation with somewhat lower coefficients (r = 0.4954 in CC, 0.3597 in MLO). In screening mammography, for CBT within the range of (7-39)mm, the NDRLs were (1.5mGy, 1.66mGy) in CC) and MLO views. For CBT in the range of (40-59)mm, the NDRLs were (1.78mGy, 1.87mGy), and for CBT in the range of (60-99)mm, the NDRLs were (2.18mGy, 2.22mGy). For diagnostic mammography, the NDRLs were established as (1.7mGy, 1.91mGy), (2.00mGy, 2.09mGy), and (2.63mGy, 2.81mGy) for CBT ranges of (7-39)mm, (40-59)mm, and (60-99)mm, respectively.

Conclusion

The NDRLs for digital screening and diagnostic mammography in Uganda have been proposed for the first time. The NDRL values in mammography should be specific to CBT ranges and mammographic views for both diagnostic and screening mammography.