bluuebunny/crossref_metadata_2025 huggingface dataset:
Virtual substrate method: synthesis and growth kinetics of 2D metal oxide nanosheets
Authors: Aiswarya S M , Chandra Somesh , Jain Ashish , Hussain Shamima , Ganesamoorthy S , Bhalerao G M , Govindaraj R
Published: April 2024

We present the experimental decomposition kinetics for the synthesis of metal oxide 2D nanosheets by the virtual substrate method. In this method, acetates of Mg and Cu were used as precursors for the growth of prototype MgO and CuO nanosheets, while the filter paper was utilized as a virtual substrate. The synthesized samples were characterized by X-ray diffraction for the phase analysis of the nanostructures, which confirms the cubic phase of MgO and monoclinic phase of CuO; with a minor Cu2O phase. Field emission scanning electron microscopy was used to determine the surface morphology of the nanosheets. Fourier transform infrared spectroscopy was utilized to identify the vibrational modes of the metal oxides and the functional groups present in the sample. Thermogravimetric analysis revealed the evolution of combustive oxidation of filter paper with the thermal decomposition of acetates situated on its surface.
Physicochemical Investigation of Synthesized Bismuth and Silver-Doped Bismuth Nanoferrites, And Their Dielectric Properties
Authors: Kannolli Amrutesh , Avinash P
Published: April 2024

Bismuth nano ferrite and silver-doped bismuth nano ferrite are synthesized by the sol-gel method. The synthesized compound is characterized through several characterization methods such as the X-ray diffraction method, Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), and UV-Visible spectral studies. The X-Ray diffraction confirms bismuth nano ferrite has a Rhombohedral structure and belongs to the R-3m space group, and the silver-doped bismuth nano ferrite has an orthorhombic structure and belongs to the Cmcm space group. The crystallite size is calculated through Scherrer’s formula, the bismuth nano ferrite has a crystallite size of 20 nm, and the silver-doped bismuth nano ferrite has a crystallite size of 36.33 nm. FTIR studies confirm the formation of ferrite and indicate the metal ion group observed the peak shift after doping in the fingerprint region. The metal ion peaks are presented at 446.7 cm−1 and 527.8 cm−1 but after doping they shifted to 453 cm−1, 534 cm−1. The UV-Visible spectral analysis identifies the change in the energy band gap through a tauc plot, initially the energy band gap of bismuth nano ferrite is about 2.79 eV but after doping it reduces to 1.61 eV. the surface morphology is determined by SEM analysis and it provides 30 nm and for the doped compound 37 nm average particle size. Dielectric study confirms doping of silver to the bismuth gives more improved results which will be helpful at the application level such as in memory devices, photocatalysis, water splitting, and gas detection.
Synthesis and characterization of NiFe2 O4 nanoparticles by tartaric acid assisted sol-gel auto-combustion method
Authors: Ningayya Patil Prabhakar , Kumar Sarvesh , Jali V M , Sahoo B
Published: April 2024

Nickel ferrite nanoparticles were synthesized by modified sol-gel auto-combustion method. The final product obtained was annealed at 600 °C. The thermal, structural, morphological, vibrational, optical and magnetic properties were studied using TGA, XRD, SEM, FTIR, UV-DRS and VSM techniques, respectively. The thermo gravimetric analysis shows three step decomposition of residual nitrate and tartrate complexes with a total weight loss of 6.69% below 600 °C. Further, there was no significant weight loss above 600 °C. XRD confirmed the spinel cubic phase with Fd3m space group. The average crystallite size was 14 nm. An agglomerated random morphology with porous flake like microstructure was observed. The vibrational analysis confirmed the presence of Ni-O, Fe-O stretching vibrational modes in the wave number range 400-600 cm−1. Tetrahedral site (kTd) and octahedral site (kOh) force constant values were 2.20×105 and 1.31×105 dynes/cm, respectively. From UV-DRS spectra, the Kubelka-Munk function was used to calculate the optical band gap and it was 1.71 eV. The magnetic saturation, retentivity and coercive field values: Ms = 22.35 emu/gm, Mr = 5.20 emu/gm, Hc = 165 Gauss were obtained from VSM analysis. The calculated magnetic moment value was 1.115 μB. The law of approach to saturation was employed to analyze the VSM data in saturation region. The calculated magneto-crystalline anisotropy constant, K1 value was 0.857×105 erg/cc.
Effect of Sn on Physical and Optical Properties of Lithium Zinc Borate Glasses
Authors: Mohamed Haneen K , Thammaiah Akshay K , Abhishek R , Shivamurthy C B , Thirumalaimurugan Vivek , Gangadaraiah Jagadeesha B , Jagannathan Abhiram
Published: April 2024

22.5 Li2O3-(20-x) ZnO-57.5B2O3 – xSnCl2 (x = 0, 0.5. 1) glasses were synthesized using the conventional melt quench technique. Glass composition with larger concentration of lithium oxide exhibits excellent transport properties. Introducing intermediate element like zinc into the matrix will lead towards slight modification in structure by not varying much in its intrinsic properties. Thus, incorporation of Sn as dopant into the matrix has tailored the physical and optical properties of glasses. In this study, it is interesting to note that, the density of the glass has reduced for 0.5 mol % SnCl2 in the matrix and on the contrary, the density of glass was found to be increased for the SnCl2 with 1 mol % concentration. It indicates that, there could be a possibility of slight modification in the structure of glasses which eventually leads towards tuning of the optical bandgap due to existence of Sn.
Dielectric relaxation studies in Sm2O3 doped boro-zinc-vanadate glasses
Authors: Ashwini D , Sankarappa T , Amarkumar M , Mohansingh H , Pallavi J , Arvind D , Raghavedra B
Published: April 2024

In this work, the conventional melting procedure was adopted to synthesize glasses with a composition of (ZnO)0.3 – (V2O5)0.3 – (B2O3)0.4-x – (Sm2O3)x, x = 0.002, 0.005, 0.007, 0.01 and 0.02 mol%. The dielectric properties of these glasses were measured. The dielectric constant (εʹ) and dielectric loss (εʹʹ) of glasses are found to vary in the range from 1.9177x102 to 3.9456x103 and from 1.5751 to 6.9095x105 respectively for the temperature range 343 K – 573 K and frequency range 50 Hz to 10 MHz. With increase of frequency, both dielectric constant and loss decreased and increased with increase of temperature. The analysis of dielectric constant and dielectric loss confirmed that the phenomenon of dielectric relaxation is mainly due to the frequency-dependent polarization mechanism. Electric modulus and impedence spectroscopy revealed non-Debye type and a single phase relaxation process. Activation energy for dc conductivity and dielectric relaxation are found to be of same size indicating that the potential barrier encountered by the charge carriers is same in both the processes. The master curves suggested that temperature-independent relaxation is occurring in the present glasses. The high values of measured dielectric parameters suggest that the present glasses are suitable in semiconducting and energy storage applications.
Synthesis and characterization of zinc doped nickel nanoferrites via sol-gel auto-combustion technique
Authors: Rayar Ashwini , Prasanna G D
Published: April 2024

Over the last few decades, numerous researchers have made significant contributions to the development of spinel ferrite owing to its unique and versatile structural, spectroscopic, and magnetic characteristics. These ferrites are extensively used in various applications such as microwaves, drug delivery, gas sensors, and electronic devices. Their technological applications require low porosity, high density, and specified microstructure. In this work, we prepared Zinc-doped Nickel nanoferrites Ni1-xZnxFe2O4 (x= 0, 0.1, 0.2, 0.3) using the sol-gel auto-combustion technique. Structural analysis of prepared samples was done using X-ray diffraction and Scanning Electron Microscopy, the elemental composition was examined using EDAX and optical studies using UV-visible spectroscopy. The average crystallite size was found in the 40.6 to 64.92 nm range. EDAX analysis confirmed the presence of expected elements in the samples. From UV-visible spectroscopy characterization studies it was observed that as particle size increases, there will be an increase in the band gap energy of ferrite nanoparticles. The Nickel-Zinc nanoferrite absorbs energy in the range of 233nm to 237nm.
Synthesis of ZnO nanorods decorating with Ag nanoparticles on flexible polyimide substrate for visible photodetector application
Authors: Nguyen Bui Gia Man , Huynh Ha Ngoc Duy , Nguyen Nhat Minh , La Phan Phuong Ha , Duy Le Thai , Dang Vinh Quang
Published: April 2024

Polyimide (PI), which have many remarkable features such as excellent mechanical strength, outstanding thermal stability, exceptional electric properties, etc, is a potential carrier for optoelectronic devices due to its abundant applications. However, because of chemical inertness and smooth surface that led to the growth of materials on this substrate being more complex than that on rigid substrate, thus, this report aims to emphasise the synthesis of ZnO NRs decorated with the Ag NPs on flexible substrate for photodetector application. In this study, we successfully synthesise ZnO NRs/Ag NPs on a flexible PI substrate by the hydrothermal method. The performance of our photodetector in visible region (395 nm) exhibits via the responsivity of the device, which recorded value of ca. 40.16 mA W−1 at 1.66 mW cm−2. With obtained results, our research can pave the way for future studies based on flexible optoelectronic devices.
Moiré-modulated band gap and van Hove singularities in twisted bilayer germanene
Authors: Bampoulis Pantelis , Castenmiller Carolien , Klaassen Dennis J , V Mil Jelle , de Boeij Paul L , Ezawa Motohiko , Zandvliet Harold J W
Published: April 2024

Twisting bilayers of two-dimensional topological insulators has the potential to create unique quantum states of matter. Here, we successfully synthesized a twisted bilayer of germanene on Ge2Pt(101) with a 21.8° twist angle, corresponding to a commensurate (√7×√7) structure. Using scanning tunneling microscopy and spectroscopy, we unraveled the structural and electronic properties of this configuration, revealing a moiré-modulated band gap and a well-defined edge state. This band gap opens at AB/BA stacked sites and closes at AA stacked sites, a phenomenon attributed to the electric field induced by the scanning tunneling microscopy tip. Our study further revealed two van Hove singularities at −0.8 eV and +1.04 eV, resulting in a Fermi velocity of (8 ± 1) × 105 m s−1. Our tight-binding results uncover a unique quantum state, where the topological properties could be regulated through an electric field, potentially triggering two topological phase transitions.
Thickness-dependent exciton behavior in two-dimensional indium selenide
Authors: Zhang Xue , Huang Hao , Zhu Yajun , Wang Aolin , Sun Shiwei , Zhou Zhijie , Zou Bingsuo , Zou Xuming
Published: April 2024

A comprehensive investigation into the exciton behaviors in indium selenide (InSe) is yet to be conducted. Here, the power factor K, which can characterize the excitonic behaviors, was determined for InSe with varying thicknesses. The photoluminescence results suggest that defects play a dominant role in the recombination of excitons with varying thicknesses. Consequently, the free exciton peak at 931 nm, which is linked to the double exciton emission behavior, becomes obscured by the presence of a bound exciton peak at 980 nm resulting from defect-induced recombination. However, at specific thicknesses and power levels, the enhancement of quantum confinement effect coupled with a reduction in defect proportion enables the observation of the peak corresponding to free exciton. Furthermore, the extracted K values from the InSe photodetectors corroborated the aforementioned findings. The results presented here provide an in-depth understanding of exciton behavior in InSe and provide theoretical underpinning for the development of InSe-based optoelectronics.
Investigation of effect of processing parameters of 3D printed NHS/EDC crosslinked carboxy methyl cellulose/gelatin hydrogels with machine learning techniques
Authors: Ege Duygu , Arıcı Şule
Published: April 2024

This study focuses on the effects of preparing conditions of gelatin/carboxymethyl cellulose (CMC) composites on their mechanical properties of gelatin/carboxymethyl cellulose (CMC) by extreme gradient boosting (XGB) machine learning algorithm. The research involved studying the effect of weight fraction of carboxymethyl cellulose (CMC) and graphene oxide (GO) as well as the concentration of ethyl(dimethylaminopropyl)carbodiimide (EDC)/ N-hydroxysuccinimide (NHS) on modulus, % strain at break and ultimate tensile strength (UTS). It also includes a correlation heatmap, feature importance assessment, model performance evaluation, and the Shapley Additive Explanation (SHAP) technique to analyze the dataset. The relationship between independent parameters and mechanical properties reveals insights into the material’s ductility, flexibility, and modulus. Feature importance demonstrates that NHS/EDC concentration has the highest impact on the mechanical properties. Increase of EDC/NHS concentration is observed to drastically elevate the modulus and UTS, however, reduces the flexibility of the nanocomposites. CMC improves flexibility but reduces UTS and modulus. GO improves % strain at break, UTS and modulus up to 1% GO, however, higher wt% of GO reduces the mechanical performance. With lower concentrations of NHS/EDC, the mechanical properties can be tailored for soft tissue engineering applications. The study highlights the importance of optimizing material compositions for tissue engineering applications.
Experimental investigation on effects of ultrasonic process parameters on the degree of impregnation of BF/PP composites
Authors: Liu Yuanyuan , Yang Yifei , He Yadong , Xin Chunling , Ren Feng , Yu Yang
Published: April 2024

The properties of basalt fiber reinforced polypropylene composites (BF/PP) were improved by ultrasonic treatment of resin building pressure to assist melt impregnation. Combined with the study of ultrasonic pressure building theory, the mechanical properties of the modified composites were analyzed using the characterization of tensile, flexural and impact strengths in response to porosity and fracture rate. The effects of ultrasonic power, frequency and distance of action on resin building pressure and composite properties were investigated. The results showed that the best effect was achieved when the ultrasonic frequency was 25 kHz, the ultrasonic power was 300 W, and the action distance was 4 mm, at which time the porosity of the prepreg was reduced to 2.99%, the fracture rate was 3.36%, and the tensile, flexural, and impact strengths were 108.73 MPa, 116.81 MPa, and 51.59 KJ.m−2.
Perspectives for III-nitride photonic platforms
Authors: Boucaud Philippe , Bhat Nagesh , Gromovyi Maksym , El Kurdi Moustafa , Reserbat-Plantey Antoine , Tuan Dau Minh , Al Khalfioui Mohamed , Alloing Blandine , Damilano Benjamin , Semond Fabrice
Published: April 2024

The development of photonic platforms for the visible or ultra-violet spectral range represents a major challenge. In this article, we present an overview of the technological solutions available on the market. We discuss the pros and cons associated with heterogeneous or monolithic integration. We specifically focus on the III-nitride platform for integrated photonics. The III-nitrides offer every building block needed for a universal platform. We discuss the additional opportunities offered by combining III-nitride semiconductors with other materials such as two-dimensional materials.
Therapeutic Trust
Authors: Carter J Adam
Published: April 2024

This chapter extends the telic normativity framework to therapeutic trust and characterizes its nature and its constitutive norms. Central to the view advanced is a distinction between two kinds of therapeutic trust—default therapeutic trust and overriding therapeutic trust—each of which derives from a distinct kind of trusting competence. The new view is shown to have advantages over some notable extant accounts of therapeutic trust, and its relation to standard (non-therapeutic) trust, as defended by Hieronymi, Frost-Arnold, and Jones.
The Passes to Florence
Authors: Havely Nick
Published: April 2024

Chapter 3 is the first of two that trace the history of the region where the routes between Bologna and Florence cross the Apennines. It was an area of strategic importance during the Second World War, since the German Gothic Line of defence closely followed the ridge. This chapter deals with the stories and reminiscences of those who fought along this section of the Gothic Line, especially the British scholar Derek Brewer and soldiers of the US Fifth Army who breached the Line at Il Giogo in September 1944. It also describes the many travellers who crossed by way of Il Giogo (between Firenzuola and Scarperia) from the Middle Ages until the mid eighteenth century, when the new road was opened over the Futa Pass, and it considers how perceptions of these mountains changed over that period.
The Passes to Florence
Authors: Havely Nick
Published: April 2024

Chapter 4 is the second of those addressing the history and perceptions of the routes over the Apennine ridge between Bologna and Florence. It begins by describing the stretch of the GEA between Il Giogo and the Passo della Futa, its convergence with the Via degli Dei walking route from Bologna, and some of the difficulties of wayfinding at this point. At the Passo della Futa World War II is again recalled by a visit to the German military cemetery; then the rest of the chapter concentrates on the travellers who crossed the pass on their way to or from Florence between the mid eighteenth century and the end of the nineteenth. Major figures include Goethe, Humphrey Davy, Beckford, Hazlitt, Fenimore Cooper, Lear, and Garibaldi, but a number of lesser known travellers are cited, and responses to Apennine landscape and the risks of travel (weather, brigandry) are a recurrent theme.
Introduction
Authors: Schellenberg J L
Published: April 2024

The Introduction explains the objectives of the book and describes its structure and content. Development is regarded as evolution that has resulted in some improvement. The book examines what various arguments from development show concerning the truth or falsity of classical Christian doctrine. Christian doctrine is conceived as holding that human beings are mired in sin, that we require deliverance and salvation, and that God has arranged for that deliverance through the sacrificial suffering, death, and resurrection of Jesus Christ, who was both a man and the divine Son of God. The Introduction notes that, as it formulates arguments against this doctrine, the book pays attention to recent social and ethical developments. The Introduction also pre-emptively answers a critique of the book’s approach, associated with the work of Tom Holland and based on the idea that Christianity is itself responsible for the forms of development here used to criticize it.
On the Divine Jesus
Authors: Schellenberg J L
Published: April 2024

This chapter introduces the Big Narrative, argues that God would have been opposed to it, and shows how we can conclude that the doctrine of the divinity of Jesus is false. The Big Narrative of the Bible centrally features important deficiencies. Given what God would always have known, God would have been opposed to it. Four arguments making use of this idea go further: if God would be opposed to the Big Narrative then God Incarnate would be opposed to it; God would not have wished to confirm the Big Narrative in the minds of people who heard of God’s action; the view of Jesus as the Son of God and as the Messiah, stands or falls with the Big Narrative; and there would have had to be some way, apart from one bound up with the Big Narrative, for a divine action of incarnation in Jesus to be justified.
What God Would Have Known
Authors: Schellenberg J L
Published: April 2024

The final chapter reconceives the arguments from development previously stated, and then shows how a new argument for the denial of theism can be formulated. This is the Argument Against Theism from the Cultural Success of Christianity. It holds that if God exists, then the salvific needs of the world are met. But if that’s so then no false salvation plan has gone into the world under God’s name and dominated the understanding of many humans for thousands of years, introducing new harms and deepening the need for real salvation. And yet this precisely is what we have given the cultural success of Christianity, which brought a supposed revelation from God bearing a misleading picture of theistic salvation that dictated the terms of salvation to a large part of human culture for 2,000 years. Thus the salvific needs of the world have not been met, and God does not exist.
Conclusion
Authors: Schellenberg J L
Published: April 2024

This short concluding statement clarifies the central position that the book is held to support, reflects on how easily Christians are prevented from seeing the relevance to that position of what God would have known, answers a query concerning what was left out of the book, and points in the direction of relevant further investigation. My position is that at least one of the twenty arguments from development formulated in previous chapters is sound. Even if only one of the arguments is right, the problem of contrary development is fatal to Christian doctrine. What God would have known can be seen to support these conclusions in several different ways. And there are interesting further questions that now suggest themselves: What might humans still do, in the religious realm, if classical Christian doctrine is intellectually a failure? What might Christians do, without ceasing to count as Christians?
National trends in prescription drug expenditures and projections for 2024
Authors: Tichy Eric M , Hoffman James M , Tadrous Mina , Rim Matthew H , Cuellar Sandra , Clark John S , Newell Mary Kate , Schumock Glen T
Published: April 2024

Purpose

To report historical patterns of pharmaceutical expenditures, to identify factors that may influence future spending, and to predict growth in drug spending in 2024 in the United States, with a focus on the nonfederal hospital and clinic sectors.

Methods

Historical patterns were assessed by examining data on drug purchases from manufacturers using the IQVIA National Sales Perspectives database. Factors that may influence drug spending in hospitals and clinics in 2024 were reviewed—including new drug approvals, patent expirations, and potential new policies or legislation. Focused analyses were conducted for biosimilars, cancer drugs, endocrine drugs, generics, and specialty drugs. For nonfederal hospitals, clinics, and overall (all sectors), estimates of growth of pharmaceutical expenditures in 2024 were based on a combination of quantitative analyses and expert opinion.

Results

In 2023, overall pharmaceutical expenditures in the US grew 13.6% compared to 2022, for a total of $722.5 billion. Utilization (a 6.5% increase), new drugs (a 4.2% increase) and price (a 2.9% increase) drove this increase. Semaglutide was the top drug in 2023, followed by adalimumab and apixaban. Drug expenditures were $37.1 billion (a 1.1% decrease) and $135.7 billion (a 15.0% increase) in nonfederal hospitals and clinics, respectively. In clinics, increased utilization drove growth, with a small impact from price and new products. In nonfederal hospitals, a drop in utilization led the decrease in expenditures, with price and new drugs modestly contributing to growth in spending. Several new drugs that will influence spending are expected to be approved in 2024. Specialty, endocrine, and cancer drugs will continue to drive expenditures.

Conclusion

For 2024, we expect overall prescription drug spending to rise by 10.0% to 12.0%, whereas in clinics and hospitals we anticipate an 11.0% to 13.0% increase and a 0% to 2.0% increase, respectively, compared to 2023. These national estimates of future pharmaceutical expenditure growth may not be representative of any health system because of the myriad of local factors that influence actual spending.
Eravacycline, an antibacterial drug, repurposed for pancreatic cancer therapy: insights from a molecular-based deep learning model
Authors: Jabarin Adi , Shtar Guy , Feinshtein Valeria , Mazuz Eyal , Shapira Bracha , Ben-Shabat Shimon , Rokach Lior
Published: April 2024

Background

Pancreatic ductal adenocarcinoma (PDAC) remains a serious threat to health, with limited effective therapeutic options, especially due to advanced stage at diagnosis and its inherent resistance to chemotherapy, making it one of the leading causes of cancer-related deaths worldwide. The lack of clear treatment directions underscores the urgent need for innovative approaches to address and manage this deadly condition. In this research, we repurpose drugs with potential anti-cancer activity using machine learning (ML).

Methods

We tackle the problem by using a neural network trained on drug–target interaction information enriched with drug–drug interaction information, which has not been used for anti-cancer drug repurposing before. We focus on eravacycline, an antibacterial drug, which was selected and evaluated to assess its anti-cancer effects.

Results

Eravacycline significantly inhibited the proliferation and migration of BxPC-3 cells and induced apoptosis.

Conclusion

Our study highlights the potential of drug repurposing for cancer treatment using ML. Eravacycline showed promising results in inhibiting cancer cell proliferation, migration and inducing apoptosis in PDAC. These findings demonstrate that our developed ML drug repurposing models can be applied to a wide range of new oncology therapeutics, to identify potential anti-cancer agents. This highlights the potential and presents a promising approach for identifying new therapeutic options.
IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network
Authors: Hu Xiaowen , Zhang Pan , Liu Dayun , Zhang Jiaxuan , Zhang Yuanpeng , Dong Yihan , Fan Yanhao , Deng Lei
Published: April 2024

Accurately delineating the connection between short nucleolar RNA (snoRNA) and disease is crucial for advancing disease detection and treatment. While traditional biological experimental methods are effective, they are labor-intensive, costly and lack scalability. With the ongoing progress in computer technology, an increasing number of deep learning techniques are being employed to predict snoRNA–disease associations. Nevertheless, the majority of these methods are black-box models, lacking interpretability and the capability to elucidate the snoRNA–disease association mechanism. In this study, we introduce IGCNSDA, an innovative and interpretable graph convolutional network (GCN) approach tailored for the efficient inference of snoRNA–disease associations. IGCNSDA leverages the GCN framework to extract node feature representations of snoRNAs and diseases from the bipartite snoRNA-disease graph. SnoRNAs with high similarity are more likely to be linked to analogous diseases, and vice versa. To facilitate this process, we introduce a subgraph generation algorithm that effectively groups similar snoRNAs and their associated diseases into cohesive subgraphs. Subsequently, we aggregate information from neighboring nodes within these subgraphs, iteratively updating the embeddings of snoRNAs and diseases. The experimental results demonstrate that IGCNSDA outperforms the most recent, highly relevant methods. Additionally, our interpretability analysis provides compelling evidence that IGCNSDA adeptly captures the underlying similarity between snoRNAs and diseases, thus affording researchers enhanced insights into the snoRNA–disease association mechanism. Furthermore, we present illustrative case studies that demonstrate the utility of IGCNSDA as a valuable tool for efficiently predicting potential snoRNA–disease associations. The dataset and source code for IGCNSDA are openly accessible at: https://github.com/altriavin/IGCNSDA.
Detection of SARS-CoV-2 B.1.1.529 (Omicron) variant by SYBR Green-based RT-qPCR
Authors: Abdel-Sater Fadi , Makki Rawan , Khalil Alia , Hussein Nader , Borghol Nada , Abi Khattar Ziad , Hamade Aline , Khreich Nathalie , El Homsi Mahoumd , Kanaan Hussein , Raad Line , Skafi Najwa , Al-Nemer Fatima , Ghandour Zeinab , El-Zein Nabil , Abou-Hamdan Mhamad , Akl Haidar , Hamade Eva , Badran Bassam , Hamze Kassem
Published: April 2024

The coronavirus disease 2019 (COVID-19) pandemic is unceasingly spreading across the globe, and recently a highly transmissible Omicron SARS-CoV-2 variant (B.1.1.529) has been discovered in South Africa and Botswana. Rapid identification of this variant is essential for pandemic assessment and containment. However, variant identification is mainly being performed using expensive and time-consuming genomic sequencing. In this study, we propose an alternative RT-qPCR approach for the detection of the Omicron BA.1 variant using a low-cost and rapid SYBR Green method. We have designed specific primers to confirm the deletion mutations in the spike (S Δ143-145) and the nucleocapsid (N Δ31-33) which are characteristics of this variant. For the evaluation, we used 120 clinical samples from patients with PCR-confirmed SARS-CoV-2 infections, and displaying an S-gene target failure (SGTF) when using TaqPath COVID-19 kit (Thermo Fisher Scientific, Waltham, USA) that included the ORF1ab, S, and N gene targets. Our results showed that all the 120 samples harbored S Δ143-145 and N Δ31-33, which was further confirmed by whole-genome sequencing of 10 samples, thereby validating our SYBR Green-based protocol. This protocol can be easily implemented to rapidly confirm the diagnosis of the Omicron BA.1 variant in COVID-19 patients and prevent its spread among populations, especially in countries with high prevalence of SGTF profile.
Real-World Patterns and Economic Burden Associated With Treatment Failure With Advanced Therapies in Patients With Moderate-to-Severe Ulcerative Colitis
Authors: Lee Scott D , Betts Keith A , Xiaoyan Du Ella , Nie Xiaoyu , Gupte-Singh Komal , Ritter Timothy
Published: April 2024

Background

Some patients lose response during treatment for moderate-to-severe ulcerative colitis (UC). We aimed to characterize real-world treatment failure patterns and associated economic burdens during use of first-line advanced therapies for UC.

Methods

IBM MarketScan Commercial and Medicare Supplemental Databases were used to identify adults initiating ≥ 1 advanced therapy for UC (January 1, 2010–September 30, 2019). Treatment failure was defined as augmentation with non-advanced therapy, discontinuation, dose escalation/interval shortening, failure to taper corticosteroids, UC-related surgery, or UC-related urgent care ≤ 12 months after treatment initiation. The index date was the date of treatment failure (treatment failure cohort) or 12 months after treatment initiation (persistent cohort). Treatment failure rates were assessed using Kaplan–Meier analyses. All-cause and UC-related healthcare resource utilization (HCRU) and costs 12 months post-index were also assessed.

Results

Analysis of treatment failure patterns included data from 6745 patients; HCRU and cost analyses included data from 5302 patients (treatment failure cohort, n = 4295; persistent cohort, n = 1007). In the overall population, 75% experienced treatment failure within the first 12 months (median: 5.1 months). Augmentation with non-advanced therapy (39%) was the most common first treatment failure event. The treatment failure cohort had significantly (P < .001) higher mean costs than the persistent cohort (all-cause, $74 995 vs $56 169; UC-related, $57 096 vs $47 347) mainly attributed to inpatient admissions and outpatient visits. Dose escalation/interval shortening accounted for the highest total costs ($101 668) across treatment failure events.

Conclusions

Advanced therapies for moderate-to-severe UC are associated with high rates of treatment failure and significant economic burden. More efficacious and durable treatments are needed.
Unconventional diagnosis of bradyarrhythmic syncope in Brugada syndrome: a case report
Authors: Esposito Francesca , Nappi Felice , Urraro Francesco , Vitillo Paolo , Rotondi Francesco
Published: April 2024

Background

The Brugada syndrome (BrS) is an inherited disorder associated with the risk of ventricular fibrillation and sudden cardiac death (SCD). The current main therapy is an implantable cardioverter-defibrillator (ICD). However, the risk stratification and management of patients remain challenging. Here, we present a case of BrS representative of the pitfalls that clinicians may encounter in the management of Brugada patients in routine clinical practice.

Case summary

A 39-year-old man with BrS and recurring syncope was implanted with a subcutaneous ICD (S-ICD) (EMBLEM MRI S-ICD, Boston Scientific). Syncope recurred some months later. Subcutaneous ICD interrogation showed no arrhythmic events, but SMART Pass (high-pass filter) deactivation was noted. A query was sent to Boston Scientific clinical service, unveiling an extremely long asystolic pause as syncope determinant. Subcutaneous ICD was explanted and replaced by conventional single chamber ICD in the pre-pectoral region.

Discussion

Brugada syndrome patients with high-risk features are candidates for ICD implantation to prevent SCD. Recent evidence highlighted that symptomatic patients carry a substantially higher risk compared with asymptomatic ones. Syncope may represent a pivotal symptom in BrS patients, but young patients with Type 1 Brugada pattern may experience syncope other than from tachyarrhythmias. Subcutaneous ICD is an advisable option in young ICD recipients to avoid lifetime complication related to standard transvenous systems. However, S-ICD lacks pacing capabilities and, therefore, is not indicated when an anti-bradycardia system is needed. The diagnostic workup of syncope in Brugada patients may be ineffective in elucidating the underlying aetiology whose understanding is essential to offer a personalized therapeutic approach.
Unlocking the potential of artificial intelligence in electrocardiogram biometrics: age-related changes, anomaly detection, and data authenticity in mobile health platforms
Authors: Mangold Kathryn E , Carter Rickey E , Siontis Konstantinos C , Noseworthy Peter A , Lopez-Jimenez Francisco , Asirvatham Samuel J , Friedman Paul A , Attia Zachi I
Published: April 2024

Aims

Mobile devices such as smartphones and watches can now record single-lead electrocardiograms (ECGs), making wearables a potential screening tool for cardiac and wellness monitoring outside of healthcare settings. Because friends and family often share their smart phones and devices, confirmation that a sample is from a given patient is important before it is added to the electronic health record.

Methods and results

We sought to determine whether the application of Siamese neural network would permit the diagnostic ECG sample to serve as both a medical test and biometric identifier. When using similarity scores to discriminate whether a pair of ECGs came from the same patient or different patients, inputs of single-lead and 12-lead medians produced an area under the curve of 0.94 and 0.97, respectively.

Conclusion

The similar performance of the single-lead and 12-lead configurations underscores the potential use of mobile devices to monitor cardiac health.
A data-centric perspective on exposomics data analysis
Authors: Chang Le , Ewald Jessica , Hui Fiona , Bayen Stéphane , Xia Jianguo
Published: April 2024

Exposomics represents a systematic approach to investigate the etiology of diseases by formally integrating individuals’ entire environmental exposures and associated biological responses into the traditional genotype-phenotype framework. The field is largely enabled by various omics technologies which offer practical means to comprehensively measure key components in exposomics. The bottleneck in exposomics has gradually shifted from data collection to data analysis. Effective and easy-to-use bioinformatics tools and computational workflows are urgently needed to help obtain robust associations and to derive actionable insights from the observational, heterogenous, and multi-omics datasets collected in exposomics studies. This data-centric perspective starts with an overview of the main components and common analysis workflows in exposomics. We then introduce six computational approaches that have proven effective in addressing some key analytical challenges, including linear modeling with covariate adjustment, dimensionality reduction for covariance detection, neural networks for identification of complex interactions, network visual analytics for organizing and interpreting multi-omics results, Mendelian randomization for causal inference, and cause-effect validation by coupling effect-directed analysis with dose-response assessment. Finally, we present a series of well-designed web-based tools, and briefly discuss how they can be used for exposomics data analysis.
Validation and forensic application of a new 36 X-STR loci multiplex system
Authors: Chen Kaiqin , Tao Ruiyang , Qu Yiling , Lu Junnan , Ping Yuan , Zhang Yilun , Chen Pengyu , Li Chengtao
Published: April 2024

X-chromosomal short tandem repeats (X-STRs) are indispensable in specific cases, distinct from autosomal and Y chromosome genetic markers. SureID® X37 is an innovative six-color fluorescence multiplex detection system that can simultaneously amplify 36 X-STR loci (including DXS6795, DXS7132, DXS8378, DXS10101, DXS10103, DXS10079, DXS10134, GATA172D05, HPRTB, DXS6810, DXS10135, DXS6797, DXS10074, DXS7424, DXS9902, DXS7423, DXS10148, DXS10162, DXS6809, GATA31E08, DXS6803, DXS10075, DXS6807, DXS10164, DXS6789, DXS10146, DXS981, DXS9895, DXS101, DXS6800 DXS907, and DXS8377) and the Amelogenin locus. In this study, we validated its suitability for forensic identification per SWGDAM (Scientific Working Group on DNA analysis methods) guidelines, including PCR conditions, precision, accuracy, case-type samples, sensitivity, repeatability, reproducibility, species specificity, stability, stutter calculation, and DNA mixtures. Additionally, 577 Han Chinese individuals were used to investigate the utility of the system in forensic population genetics. The results indicated that the system is sensitive, stable, and reliable, and is suitable for typical forensic case. Subsequent population investigations confirmed that it serves as a potent supplementary tool in forensic applications.
Texture analysis of apparent diffusion coefficient maps: can it identify nonresponse to neoadjuvant chemotherapy for additional radiation therapy in rectal cancer patients?
Authors: Wu Qianyu , Yi Yongju , Lai Bingjia , Li Jiao , Lian Yanbang , Chen Junhong , Wu Yue , Wang Xinhua , Cao Wuteng
Published: April 2024

Background

Neoadjuvant chemotherapy (NCT) alone can achieve comparable treatment outcomes to chemoradiotherapy in locally advanced rectal cancer (LARC) patients. This study aimed to investigate the value of texture analysis (TA) in apparent diffusion coefficient (ADC) maps for identifying non-responders to NCT.

Methods

This retrospective study included patients with LARC after NCT, and they were categorized into nonresponse group (pTRG 3) and response group (pTRG 0–2) based on pathological tumor regression grade (pTRG). Predictive texture features were extracted from pre- and post-treatment ADC maps to construct a TA model using RandomForest. The ADC model was developed by manually measuring pre- and post-treatment ADC values and calculating their changes. Simultaneously, subjective evaluations based on magnetic resonance imaging assessment of TRG were performed by two experienced radiologists. Model performance was compared using the area under the curve (AUC) and DeLong test.

Results

A total of 299 patients from two centers were divided into three cohorts: the primary cohort (center A; n = 194, with 36 non-responders and 158 responders), the internal validation cohort (center A; n = 49, with 9 non-responders) and external validation cohort (center B; n = 56, with 33 non-responders). The TA model was constructed by post_mean, mean_change, post_skewness, post_entropy, and entropy_change, which outperformed both the ADC model and subjective evaluations with an impressive AUC of 0.997 (95% confidence interval [CI], 0.975–1.000) in the primary cohort. Robust performances were observed in internal and external validation cohorts, with AUCs of 0.919 (95% CI, 0.805–0.978) and 0.938 (95% CI, 0.840–0.985), respectively.

Conclusions

The TA model has the potential to serve as an imaging biomarker for identifying nonresponse to NCT in LARC patients, providing a valuable reference for these patients considering additional radiation therapy.
Inhaled Pollutants of the Gero-Exposome and Later-Life Health
Authors: Finch Caleb E , Thorwald Max A
Published: April 2024

Inhaled air pollutants (AirP) comprise extraordinarily diverse particles, volatiles, and gases from traffic, wildfire, cigarette smoke, dust, and various other sources. These pollutants contain numerous toxic components, which collectively differ in relative levels of components, but broadly share chemical classes. Exposure and health outcomes from AirP are complex, depending on pollutant source, duration of exposure, and socioeconomic status. We discuss examples in the current literature on organ responses to AirP, with a focus on lung, arteries, and brain. Some transcriptional responses are shared. It is well accepted that AirP contributes to Alzheimer’s disease and other neurodegenerative conditions in the Gero-Exposome. However, we do not know which chemical compounds initiate these changes and how activation of these transcriptional pathways is further modified by genetics and prenatal development.
Large-scale genomic survey with deep learning-based method reveals strain-level phage specificity determinants
Authors: Yang Yiyan , Dufault-Thompson Keith , Yan Wei , Cai Tian , Xie Lei , Jiang Xiaofang
Published: April 2024

Background

Phage therapy, reemerging as a promising approach to counter antimicrobial-resistant infections, relies on a comprehensive understanding of the specificity of individual phages. Yet the significant diversity within phage populations presents a considerable challenge. Currently, there is a notable lack of tools designed for large-scale characterization of phage receptor-binding proteins, which are crucial in determining the phage host range.

Results

In this study, we present SpikeHunter, a deep learning method based on the ESM-2 protein language model. With SpikeHunter, we identified 231,965 diverse phage-encoded tailspike proteins, a crucial determinant of phage specificity that targets bacterial polysaccharide receptors, across 787,566 bacterial genomes from 5 virulent, antibiotic-resistant pathogens. Notably, 86.60% (143,200) of these proteins exhibited strong associations with specific bacterial polysaccharides. We discovered that phages with identical tailspike proteins can infect different bacterial species with similar polysaccharide receptors, underscoring the pivotal role of tailspike proteins in determining host range. The specificity is mainly attributed to the protein’s C-terminal domain, which strictly correlates with host specificity during domain swapping in tailspike proteins. Importantly, our dataset-driven predictions of phage–host specificity closely match the phage–host pairs observed in real-world phage therapy cases we studied.

Conclusions

Our research provides a rich resource, including both the method and a database derived from a large-scale genomics survey. This substantially enhances understanding of phage specificity determinants at the strain level and offers a valuable framework for guiding phage selection in therapeutic applications.
Piloting racial bias training for hospital emergency department providers treating patients with opioid use disorder
Authors: Gibbons Jason B , Harris Samantha J , Sugarman Olivia K , Hulsey Eric G , Rwan Julie , Rosner Esther M , Saloner Brendan
Published: April 2024

Racial disparities in opioid overdose have increased in recent years. Several studies have linked these disparities to health care providers’ inequitable delivery of opioid use disorder (OUD) services. In response, health care policymakers and systems have designed new programs to improve equitable OUD care delivery. Racial bias training has been 1 commonly utilized program. Racial bias training educates providers about the existence of racial disparities in the treatment of people who use drugs and the role of implicit bias. Our study evaluates a pilot racial bias training delivered to 25 hospital emergency providers treating patients with OUDs in 2 hospitals in Detroit, Michigan. We conducted a 3-part survey, including a baseline assessment, post-training assessment, and a 2-month follow-up to evaluate the acceptability and feasibility of scaling the racial bias training to larger audiences. We also investigate preliminary data on changes in self-awareness of implicit bias, knowledge of training content, and equity in care delivery to patients with OUD. Using qualitative survey response data, we found that training participants were satisfied with the content and quality of the training and especially valued the small-group discussions, motivational interviewing, and historical context.
The transcription factor CpMYB62 controls the genetic network that leads to the determination of female flowers in Cucurbita pepo
Authors: Segura María , García Alicia , Gamarra German , Benítez Álvaro , Iglesias-Moya Jessica , Martínez Cecilia , Jamilena Manuel
Published: April 2024

In monoecious species, female flowering constitutes the developmental process that determines the onset and production of fruit and is therefore closely related to crop yield. This article presents the identification and phenotypic and molecular characterization of myb62, an ethylmethane sulfonate loss-of-function mutation that completely blocks the female floral transition, converting all female flowers into male flowers. BSA-seq analysis coupled with WGS showed that myb62 corresponds to a C>T transition in the coding region of the gene CpMYB62, generating a premature stop codon and a truncated transcription factor without its N-terminal effector domain. The myb62 phenotype was partially rescued by exogenous ethylene application, indicating that the function of CpMYB62 is mediated by ethylene. Different evidence supports this conclusion: first, the reduced ethylene production of the mutant, and second, the male flower productive phenotype of the double mutant between myb62 and the ethylene-insensitive mutant etr2b, which demonstrated that myb62 is epistatic over etr2b. Furthermore, transcriptomic analysis of WT and myb62 apical shoots confirmed that CpMYB62 regulates master sex-determining genes, upregulating those encoding the ethylene biosynthesis enzymes CpACO2B and CpACS27A and those encoding for transcription factors that promote the development of carpels(CpCRC), but downregulating those involved in the arrest of carpels (CpWIP1), In the gene network controlling sex determination in cucurbits, CpMYB62 occupies the most upstream position, activating ethylene and other sex determining genes involved in female flower determination in Cucurbita  pepo.