bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quartz textures, trace elements, fluid inclusions, and in situ oxygen isotopes from Aktogai porphyry Cu deposit, Kazakhstan
Authors: Li Changhao , Shen Ping , Seltmann Reimar , Zhang Di , Pan Hongdi , Seitmuratova Eleonora 
Published: June 2024

Abstract
The Paleozoic Aktogai Group in Kazakhstan ranks among the 30 largest porphyry Cu deposits globally. The Aktogai deposit is the largest one in the Aktogai Group and is characterized by intensive potassic alteration where the dominant orebody occurred. However, its mineralization processes still need to be clarified. Our investigation focused on the texture, trace elements, fluid inclusions, and in situ oxygen isotopes of the quartz from the ore-related tonalite porphyry and associated potassic alteration at Aktogai to trace the deposit’s mineralization processes. Ti-in-quartz thermobarometry, fluid inclusion microthermometry, and geological characteristics indicate that the ore-related magma at Aktogai originated from a shallow magma chamber at ∼1.9 ± 0.5 kbar (∼7.2 ± 1.9 km) and intruded as the tonalite porphyry stock at ∼1.7–2.4 km. The potassic alteration and associated Cu mineralization comprise five types of veins (A1, A2, B1, B2, and C) and two types of altered rocks (biotite and K-feldspar). Among them, nine types of hydrothermal quartz were identified from early to late: (1) VQA1 in A1 veins and RQbt in biotite-altered rocks; (2) VQA2 in A2 veins and RQkfs in K-feldspar altered rocks; (3) VQB1 in B1 veins and VQB2E in B2 veins; and (4) quartz associated with Cu-Fe sulfides (VQB2L, VQBC, and VQC) in B and C veins. Titanium contents of the quartz decreased, while Al/Ti ratios increased from early to late. Fluid inclusion microthermometry and mineral thermometers reveal that VQA1, RQbt, and hydrothermal biotite formed under high-temperature (∼470–560 °C) and ductile conditions. VQA2, RQkfs, VQB1, and hydrothermal K-feldspar formed during the transition stage from ductile to brittle, with temperatures of ∼350–540 °C. The rapid decrease in pressure from lithostatic to hydrostatic pressure led to fluid boiling and minor involvement of meteoric water (∼11–14%) in the mineralizing fluid. Extensive recrystallization in VQA1 to VQB1 was associated with repeated cleavage and healing of the intrusion. With cooling, K-feldspar decomposition and hydrolysis increased. Fluid cooling and water-rock reactions resulted in the co-precipitation of Cu-Fe sulfides, white mica, chlorite, VQBC, and VQC at temperatures of ∼275–370 °C and brittle conditions. The Paleozoic Aktogai deposit exhibits formation depths and fluid evolution processes similar to Mesozoic and Cenozoic porphyry Cu deposits worldwide. The close association between Cu-Fe sulfides and later quartz formed under intermediate-temperature conditions at Aktogai implies that Cu-Fe sulfides are not precipitated under early high-temperature conditions in porphyry Cu deposits.
Leveraging Artificial Intelligence for Synergies in Drug Discovery: From Computers to Clinics
Authors: Arora Priyanka , Behera Manaswini , Saraf Shubhini A. , Shukla Rahul 
Published: June 2024

:
Over the period of the preceding decade, artificial intelligence (AI) has proved an outstanding performance
in entire dimensions of science including pharmaceutical sciences. AI uses the concept of machine
learning (ML), deep learning (DL), and neural networks (NNs) approaches for novel algorithm and hypothesis
development by training the machines in multiple ways. AI-based drug development from molecule identification
to clinical approval tremendously reduces the cost of development and the time over conventional methods.
The COVID-19 vaccine development and approval by regulatory agencies within 1-2 years is the finest
example of drug development. Hence, AI is fast becoming a boon for scientific researchers to streamline their
advanced discoveries. AI-based FDA-approved nanomedicines perform well as target selective, synergistic
therapies, recolonize the theragnostic pharmaceutical stream, and significantly improve drug research outcomes.
This comprehensive review delves into the fundamental aspects of AI along with its applications in the
realm of pharmaceutical life sciences. It explores AI's role in crucial areas such as drug designing, drug discovery
and development, traditional Chinese medicine, integration of multi-omics data, as well as investigations
into drug repurposing and polypharmacology studies.
Emerging Role of Sorting Nexin 17 in Human Health and Disease
Authors: Chen Juan , Su Yan-Hong , Wang Meng , Zhang Yi-Chen 
Published: June 2024

:
The distortion of the cellular membrane transport pathway has a profound impact on
cell dynamics and can drive serious physiological consequences during the process of cell sorting.
SNX17 is a member of the Sorting Nexin (SNX) family and plays a crucial role in protein sorting
and transport in the endocytic pathway. SNX17, SNX27, and SNX31 belong to the SNX-FERM
subfamily and possess the FERM domain, which can assist in endocytic transport and lysosomal
degradation. The binding partners of SNX27 have been discovered to number over 100, and
SNX27 has been linked to the development of Alzheimer's disease progression, tumorigenesis,
cancer progression, and metastasis. However, the role and potential mechanisms of SNX17 in human
health and disease remain poorly understood, and the function of SNX17 has not been fully
elucidated. In this review, we summarize the structure and basic functions of SNX protein, focusing
on providing current evidence of the role and possible mechanism of SNX17 in human neurodegenerative
diseases and cardiovascular diseases.
Emerging Anti-Inflammatory Attributes of Curcumin: A Novel Paradigm
and Ameliorative Attributes for the Treatment of Osteoarthritis
Authors: Bajpai Priyanka , Chandra Phool 
Published: June 2024

Abstract::
Strong oxidant, curcumin, is diferuloyl methane; a member of the class of phenols
known as curcuminoids that give Indian medicinal plants their characteristic turmeric-yellow hue.
Over 5000 years ago, curcumin was first employed in the traditional Indian medical system. A
growing amount of investigation reveals that curcumin has several pharmacological characteristics,
including anticancer, hepatoprotective, anti-inflammatory, antioxidant, and antibacterial properties.
Clinical tests revealed no harm, but some participants did have moderate nausea or diarrhea.
A degenerative joint condition known as osteoarthritis affects elderly populations all over
the world. It has a chronic inflammatory etiology, which contributes to chondrocyte loss that results
in a thinner surface of cartilage at the affected joints. Curcumin has been scientifically demonstrated
to exhibit medicinal benefits for osteoarthritis (OA), and further research is being conducted
on the numerous ways through which it suppresses inflammation and slows the progression
of ailments. Clinical and preclinical studies suggest the potential efficacy of curcumin in managing
osteoarthritis, warranting further investigation. With emphasis on the mechanisms associated,
this review seeks to completely outline the clinical effectiveness of curcumin using data from
a variety of scientific studies that have been published so far.
A Dynamic Context Encoder Network for Liver Tumor Segmentation
Authors: Liu Jun , Fang Jing , Jiang Tao , Zhou Chaochao , Shao Liren , Song Yusheng 
Published: June 2024

Background:
Accurate segmentation of liver tumor regions in medical images is of great significance for clinical diagnosis and the planning of surgical
treatments. Recent advancements in machine learning have shown that convolutional neural networks are powerful in such image processing while
largely reducing human labor. However, the variable shape, fuzzy boundary, and discontinuous tumor region of liver tumors in medical images
bring great challenges to accurate segmentation. The feature extraction capability of a neural network can be improved by expanding its
architecture, but it inevitably demands more computing resources in training and hyperparameter tuning.

Methods:
This study presents a Dynamic Context Encoder Network (DCE-Net), which incorporates multiple new modules, such as the Involution Layer,
Dynamic Residual Module, Context Extraction Module, and Channel Attention Gates, for feature extraction and enhancement

Results:
In the experiment, we used a liver tumor CT dataset of LiTS2017 to train and test the DCE-Net for liver tumor segmentation. The experimental
results showed that the four evaluation indexes of the method, precision, recall, dice, and AUC, were 0.8961, 0.9711, 0.9270, and 0.9875,
respectively. Furthermore, our ablation study reported that the accuracy and training efficiency of our network were markedly superior to the
networks without involution or dynamic residual modules.

Conclusion:
Therefore, the DCE-Net proposed in this study has great potential for automatic segmentation of liver lesion tumors in the clinical diagnostic
environment.
Diversity of Actinomycetes Isolated from Peat Soil of Undistrubed Forest and Pineapple Plantation in Sessang, Sarawak
Authors: Heng Jeffrey Lim Seng , Hamzah Halizah , Nejis Norzaimawati Aman 
Published: June 2024

Peatland plays an important role not just as a carbon store but also in facilitating the flux of greenhouse gasses into the atmosphere. Apart from that, peatland is also home to a diverse population of microorganisms such as bacteria, fungi, and actinomycetes. Actinomycetes were known to be one of the most ubiquitous microbes that can be found in most of the soil types including peat soil. In this study, seventy isolates of actinomycetes were isolated from the peat soil using the soil dilution method. The 70 isolates of actinomycetes were later screened for their ability to produce secondary metabolites and antimicrobial activities using the agar diffusion method before the selected potential isolates were identified by targeting their 16S rRNA region. The results obtained showed 34.3% produce cellulase followed by, 12.8, 31.7, 80.0, and 51.4% for mannanase, xylanase, lipase, and protease respectively. The percentage of actinomycetes producing antimicrobial activity was 27.1 and 21.4% for Ralstonia solanacearum and Colletotrichum gleosporioides respectively. All the selected isolates of actinomycetes were identified as belonging to the genus of Streptomycetes spp. The potential actinomycetes were stored in freeze-dried form for future usage. This study showed that more diverse population of actinomycetes was obtained from the undisturbed forested peat soil area ecosystem compared to the agricultural peat soil area.
100-OR: Investigating the Mechanisms of Cross Talk between Endocrine Beta Cells and Pericytes in Pancreatic Islets
Authors: MATEUS GONCALVES LUCIANA , PEREIRA ELIZABETH , ALMACA JOANA 
Published: June 2024

Introduction: Islets are small endocrine organs scattered throughout the exocrine pancreas. Although endocrine and exocrine tissues share their vascular networks, a selective increase in islet blood flow is observed upon increases in glycemia. We showed that pericytes mediate changes in islet blood flow. The aim of this study was to determine whether glucose affects directly islet pericytes or indirectly by changing endocrine cell activity and stimulating the release of vasoactive factors which act on pericytes.
Methods: To manipulate (acutely and chronically) endocrine beta cells without changing systemic glycemia, we injected adeno-associated viruses encoding excitatory designer receptors exclusively activated by designer drugs (DREAAD) under the insulin promoter. Also we treated mice with multiple low doses of the beta cell toxin streptozotocin (5 days - 50 mg/kg/day) for 2 weeks, causing only glucose intolerance. We used mice that express a genetically encoded [Ca2+]i indicator in pericytes to monitor pericyte activity.
Results: We found that acute activation of beta cells with the DREAAD agonist clozapine decreased [Ca2+]i in islet pericytes in vivo (exteriorized pancreas) and ex vivo (living pancreas slices). Blocking adenosine and serotonin receptors with specific receptor antagonists rescued the inhibitory effects of clozapine. Chronic ablation of beta cells with streptozotocin abolished the glucose-dependent decrease in pericyte [Ca2+]i and dilation of islet capillaries in pancreas slices.
Conclusions: Our study indicates that beta cells participate in the acute regulation of islet blood flow. By releasing vasoactive factors, such as adenosine and serotonin, beta cell activation decreases islet pericyte activity which results in capillary dilation and increased blood flow. Endocrine cell dysfunction that occurs during the development of diabetes may affect islet pericyte and vascular responses, impairing hormone release into circulation.

Disclosure
L. Mateus Goncalves: None. E. Pereira: None. J. Almaca: None.

Funding
National Institutes of Health (5R01DK133483-02 - J.A.)Helmsley Charitable Trust George Eisenbarth Pilot Award for nPOD team Science (J.A.)2022 Stanley Glaser Award from the University of Miami (J.A.).
1033-P: Quantifying Price Elasticity of Demand for Insulin among Medicare Beneficiaries
Authors: GUAN DAWEI , LI PIAOPIAO , JIAO TIANZE , HU XIN , ZHANG YONGKANG , CHEHAL PUNEET K. , LEE JIEUN , VENKAT NARAYAN K M , ALI MOHAMMED K. , SHAO HUI 
Published: June 2024

Background: Significant policy efforts have been implemented to lower the out-of-pocket payments (OOP) for insulin to lower access barriers and enhance adherence. We employed a machine learning approach to explore the relationship between OOP and insulin adherence among Medicare beneficiaries.
Methods: 48,613 Medicare beneficiaries with continuous use of long-acting insulin analog were identified from Medicare Fee-for-Service data (2017-2019). People covered by low-income subsidy programs and Medicaid were excluded. Adherence was measured by the proportion of days covered (PDC) by insulin in each year, and monthly OOP for a 30-day supply of insulin was estimated at a plan level. We used a localized fixed-effect model with recursive partitioning to depict the local response of OOP changes on PDC changes at different levels of baseline OOP.
Results: For individuals with monthly OOP exceeding $150, a 1.51% increase in PDC (95%CI: 1.03% to 1.99%) with every $10 reduction was observed, and for those with monthly OOP between $75 and $150, every $10 reduction correlated with a 0.69% increase in PDC (95%CI: 0.43% to 0.94%). For those with monthly OOP below $75, the further reduction did not impact the PDC.
Conclusion: The price elasticity of demand for insulin is non-linear. Reducing monthly OOP for insulin to levels lower than the cut points is vital to remove the financial barrier to adherence and ensure access to proper care.

Disclosure
D. Guan: None. P. Li: None. T. Jiao: None. X. Hu: Research Support; PhRMA Foundation. Y. Zhang: None. P.K. Chehal: None. J. Lee: None. K. Narayan: None. M.K. Ali: Advisory Panel; Eli Lilly and Company. H. Shao: Consultant; Eli Lilly and Company.
1036-P: Cost-Effectiveness of Real-Time CGM vs. Self-Monitoring of Blood Glucose in People with Type 2 Diabetes on Intensive Insulin Therapy in Australia
Authors: ALSHANNAQ HAMZA , AHMED MOIN , NORMAN GREGORY J. , SIMMONS DAVID 
Published: June 2024

Introduction: Clinical studies show RT-CGM systems improve glucose management in people with T2D on intensive insulin therapy (IIT). Reimbursement for RT-CGM in Australia is currently limited to people with T1D. Our analysis examines the cost-effectiveness of RT-CGM for people with T2D IIT in Australia.
Methods: We used the IQVIA Core Diabetes Model to simulate diabetes clinical outcomes and direct medical costs over a lifetime horizon from an Australian payor perspective. A large retrospective cohort study provided the cohort characteristics and treatment effects. The adjusted difference in A1C reduction was -0.56% for RT-CGM, severe hypoglycemic events rates of 0.04 and 0 Per Person-Year (PPY) for SMBG and RT-CGM, respectively, and DKA rates of 0.025 and 0 PPY, respectively. The costs of CGM are based on the Dexcom G6 RT-CGM list price in Australia. A utility for the avoidance of finger sticks (0.03) and fear of hypoglycemia reduction (0.025) were applied to users of RT-CGM.
Results: RT-CGM users are projected to have higher quality-adjusted life years (QALYs) by 0.621 with AUD 14,117 incremental costs, and an incremental cost-effectiveness ratio (ICER) of 22,736, below the AUD 50,000 willingness-to-pay threshold for Australia. Microvascular and macrovascular outcomes projections indicate that RT-CGM use results in a relative reduction in diabetes eye, renal, neuropathy, and cardiovascular complications of 17.7%, 21.1%, 8.7%, and 2.5% respectively. Sensitivity analysis scenarios of RT-CGM cost reductions of 10%, 20%, and 30% resulted in ICERs of 17,976, 13,220, and 8,464, respectively. RT-CGM remained cost-effective even when its costs were increased by 30%.
Conclusion: The use of RT-CGM systems for diabetes management in people with T2D on intensive insulin therapy results in significant cost savings due to the reduction of diabetes complications. These findings support expanding reimbursement for RT-CGM in Australia.

Disclosure
H. Alshannaq: Employee; Dexcom, Inc. Stock/Shareholder; Unicycive Therapeutics. M. Ahmed: None. G.J. Norman: Employee; Dexcom, Inc. D. Simmons: Speaker's Bureau; Abbott. Consultant; Sanofi. Speaker's Bureau; Ascensia Diabetes Care. Other Relationship; Ascensia Diabetes Care, Boehringer-Ingelheim. Research Support; Dexcom, Inc. Speaker's Bureau; Novo Nordisk. Research Support; Wests Club, NSW, Australia, Roche Diabetes Care.
1049-P: Clustering the U.S. Population into Social Determinants of Health (SDOH) Subgroups—A Machine-Learning Approach
Authors: LEE JIEUN , XUE QIAOCHU , LI PIAOPIAO , BETH WEBER MARY , XI YUANZHE , GARCIA GIAN-GABRIEL , ALI MOHAMMED K. , SHAO HUI 
Published: June 2024

Introduction: An increasing emphasis has been placed on addressing SDOH needs. However, SDOH encompass a wide range of intercorrelated social constructs, and these needs often have deeper roots and correlations with one another. This study aims to leverage advanced machine learning algorithms to cluster the US population into groups with similar SDOH characteristics, providing valuable insights into the intricate landscape of SDOH needs.
Methods: Survey data on individual-level SDOH and linked electronic health records from 28,778 participants of the All of Us research program is used. An extreme gradient boosting algorithm was performed to choose and rank the forty most influential variables out of 266, and then we run the PAM-lite to determine the optimal number of variables and clusters.
Results: Clustering the pre-retirees (45-64) and the elderly (65+) revealed six distinct groups (Table). Insurance, race/ethnicity, and neighborhood safety played a dominating role in clustering pre-retirees into distinct SDOH groups. However, these factors gave way to partnerships and religion among the elderly, signifying a shift in the determinants of SDOH clusters. Clusters with higher SDOH status had substantial lower rates of T2D, Obesity (chronic), and Pneumonia (infectious).
Conclusion: Findings can inform the development of targeted SDOH screening and interventions.

Disclosure
J. Lee: None. Q. Xue: None. P. Li: None. M. Weber: None. Y. Xi: None. G. Garcia: None. M.K. Ali: Advisory Panel; Eli Lilly and Company. H. Shao: Consultant; Eli Lilly and Company.
1052-P: Diabetes and Financial Well-Being—Differential Hardship among Vulnerable Populations
Authors: JACOBS MOLLY M. , ELLIS CHARLES , EVANS ELIZABETH 
Published: June 2024

Background: The ability to meet financial obligations, known as “financial well-being,” is associated with unexpected health events and expenditures. Using the Consumer Financial Protection Bureau’s (CFPB) Financial Well-Being (FWB) Scale, we evaluated the impact of diabetes on FWB and estimated the differential effects among racial and ethnic groups.
Methods: Using the Understanding America Survey (UAS) we identified adults with self-reported diabetes diagnoses. Panel data, mixed effects regression models assessed the association between diabetes and FWBS among racial and ethnic population subgroups. Models included sex, age, marital status, household size, income, education, race/ethnicity, insurance, body mass index (BMI), employment, and insurance. Racial and ethnic differentials were captured using group-condition interactions.
Results: Whites [Mean (M)=67.66, Standard Deviation (SD)=22.63] and Other racial groups (M=67.99, SD=18.45) had the highest FWBS, followed by Hispanics (M=59.31, SD=22.78), and Blacks (M=55.86, SD=25.67). However, Blacks (17.06%) had the highest prevalence of diabetes followed by Whites (12.2%), Other racial groups (10.7%), and Hispanics (10.0%). The analysis showed that, compared to Whites, Blacks [β=-5.53, Standard Error (SE)=0.71] and Hispanics (β=-2.08, SE=0.63) have significantly lower FWBS. Compared to males, females (β=-4.45, SE=0.41) had lower FWBS. Additionally, those who were married (β=3.99, SE=0.41) and earning above $75,000 (β=2.87, SE=0.24) had comparatively higher FWBS. Regression results indicated that FWBS of individuals with diabetes was 3.97 points lower (SE=0.72), on average, than those without diabetes. Furthermore, the FWBS of Blacks with diabetes (β=-3.02, SE=1.25) was even lower than Blacks without diabetes.
Conclusions: Results suggest disparities in the financial ramifications of diabetes among women, Blacks, and other marginalized populations.

Disclosure
M.M. Jacobs: None. C. Ellis: None. E. Evans: None.
1055-P: Are the Direct Health Care Costs of Fractures Higher in Patients with Type 2 Diabetes?
Authors: KVIST ANNIKA V. , FROST MORTEN , BURDEN ANDREA M. , VESTERGAARD PETER , KRISTRENSEN TROELS 
Published: June 2024

Introduction & Objective: Patients with type 2 diabetes (T2D) have an increased risk of sustaining a fracture, and risks of nonunion, impaired fracture healing, and post-fracture complications are higher in T2D. It is largely unknown how T2D affects the cost of fractures. This study aims to estimate the cost of fractures in T2D compared to persons without diabetes, and secondly to analyze potential drivers of fracture costs. We hypothesized that cost of fractures in patients with T2D are higher than in the nondiabetic background population.
Methods: This study analyses patients in Denmark aged 18+ with a hip, humerus, forearm, foot, or ankle fracture in the period 2011-2015. Persons with polycystic ovary syndrome (PCOS), with other types of diabetes, with T2D diagnosed after fracture, and persons emigrating within the follow-up period were excluded. Patients with T2D were matched with patients without diabetes based on fracture site, sex, age, and Charlson Comorbidity Index (CCI) Score. The direct healthcare costs of fractures for T2D and controls were estimated within the first year after a fracture, and the medians were tested using Mann-Whitney U-test.
Results: In this study 5890, 3921, 5174, 2592, and 2229 cases of hip, humerus, forearm, foot, and ankle fractures, respectively, were matched 1:1 with persons without diabetes. More females than males sustained fractures with the highest prevalence (71.8%) for hip fractures and the lowest prevalence (56.7%) for foot fractures. The median age was highest for hip fractures (80 years) and lowest for foot fractures (62 years). The direct healthcare cost within one year after fracture was higher among patients with T2D compared to controls for hip (€10,733 vs. €10,585, p=0.014), humerus (€1,389 vs. €1,138, p&lt;0.0001), forearm (€951 vs. €947, p=0.022), foot (€565 vs. €443, p&lt;0.0001), and ankle fractures (€1,968 vs. €1,063, p&lt;0.0001).
Conclusion: The direct healthcare costs of fractures were higher for T2D.

Disclosure
A.V. Kvist: None. M. Frost: Research Support; Novo Nordisk A/S. Stock/Shareholder; Novo Nordisk A/S. A.M. Burden: None. P. Vestergaard: None. T. Kristrensen: None.

Funding
European Union’s Horizon 2020 research and innovation program under the H2020 Marie Skłodowska-Curie Actions grant 860898.