bluuebunny/crossref_metadata_2025 huggingface dataset:
KEJADIAN COVID-19 BERDASARKAN KARAKTERISTIK PENGUNJUNG POLI ISPA PUSKESMAS PERAMPUAN LOMBOK BARAT
Authors: Kisid Kristiani , Endy Bebasari Ardhana Putri
Published: May 2023

The Covid-19 pandemic, which began in early 2020, has affected more than 3 million people in Indonesia. All health services are mobilized for p revention and treatment. The Public Health Center of Perampuan in West Lombok is no exception, which carries out a screening program for suspected visitors as visitors. In mid-2021, when a new variant of covid-19 emerged, namely the delta variant, visitors to the Poli ISPA were known to experience an increase in their covid-19 status through the Rapid Diagnostic Test (RDT) antigen. The purpose of this study was to describe the characteristics of poly ISPA visitors who received a COVID-19 swab examination and to find out whether there was a relationship between these characteristics and the incidence of Covid-19 at the Perampuan Health Center.

 

The research design is descriptive retrospective because it uses secondary data from the registration book of Poli ISPA in Public Health Center of  Perampuan. A total of 183 samples were taken from the total population, namely those who received an RDT antigen swab examination. The statistical analysis test used to find the relationship was the chi square test (?=5%).

 

The result of this research is that most of the characteristics of the visitors to the ARI poly at the Perampuan Health Center are mostly in the age group category of 18 years and over, working as employees both public and private, and male. The number of cases of covid-19 there is 52%.

 

The conclusion of this study is that there is no relationship between all characteristics of visitors to the ARI polyclinic as measured by the incidence of Covid-19 at the Perampuan Public Health Center (p>0.05). It is better if the Perampuan Health Center continues to carry out the program for handling and preventing this COVID-19 disease because this disease attacks all levels of society equally regardless of age, gender, and type of work.

 

Keywords: Covid-19, Public health center, age, sex
STATUS KESEHATAN LANSIA DI DESA PENIMBUNG KABUPATEN LOMBOK BARAT
Authors: Supinganto Agus
Published: May 2023

ABSTRACT

Introduction: A person's health status is manifested by the four dimensions of physical, mental, social and economic health that influence each other in realizing a person's level of health. Lifestyle is the most important factor that greatly affects health status. The purpose of this study was to determine the health status of the elderly in Penimbung Village, West Lombok Regency. Research method: this uses a descriptive quantitative method with a survey design approach. Sampling was done by random sampling technique. The number of samples in this study were 175 respondents. Results: The results showed the frequency distribution of the elderly, namely: 33.1% dizziness, coughing, 13.1%, tingling, 13.14%., shortness of breath, 6.3%, others 17.1%, distribution of the elderly by type the disease suffered, namely hypertension 40.6%, shortness of breath, 6.8%, diabetes, 10.2%, stroke, 1.1%, gout, 23.4%, others, 17.7% . The KIE program for the elderly collaborates with educational institutions and promotes healthy lifestyles by reducing the consumption of foods that contain a lot of salt, high fat, alcoholic beverages, nuts, and not smoking as well as increasing the routine of sports activities.

Keywords: Elderly; Health Status

ABSTRAK

 

Pendahuluan:Status kesehatan seseorang terwujud oleh ke empat dimensi kesehatan fisik, mental, sosial dan ekonomi yang saling memengaruhi dalam mewujudkan tingkat kesehatan seseorang.  Gaya hidup merupakan faktor terpenting yang sangat mempengaruhi status kesehatan.Tujuan penelitian: ini adalah untuk mengetahui setatus kesehatan Lansia di Desa Penimbung Kabupaten Lombok Barat. Metode penelitian: ini menggunakan metode kuantitatif deskriptip dengan pendekatan desain Survey. Pengambilan sampel dilakukan dengan tehnik Random Sampling. Jumlah sampel dalam penelitian ini adalah 175 responden.  Hasil: Hasil penelitian menunjukan distribusi frekwensi Lansia yaitu:  pusing  33,1%, batuk, 13,1%, kesemutan,13,14%., sesak, 6,3%, lain-lain 17,1%, distribusi Lansia berdasarkan jenis penyakit yang diderita yaitu , hipertensi 40,6%, sesak napas, 6,8%,  kencing manis, 10,2%, stroke, 1,1%, asam urat, 23,4%, lain-lain, 17,7%. Program KIE untuk Lansia bekerjasama dengan institusi pendidikan dan peningkatan gaya hidup yang sehat  dengan cara mengurangi konsumsi makanan yang mengandung banyak garam, berlemak tinggi, minuman beralkohol, kacang-kacangan, dan tidak merokok serta meningkatkan rutinitas aktivitas olahraga.

Kata Kunci: Lansia; Status Kesehatan
PENGARUH EDUKASI FAMILY CENTERED MATERNITY CARE (FCMC) MENGGUNAKAN WHATSAPP DAN BOOKLET TERHADAP KECEMASAN IBU HAMIL PADA MASA PANDEMI DI KOTA BIMA
Authors: Ardhana Putri Endy Bebasari , Efi Nurmala  , Kristiani Murti Kisid
Published: May 2023

Pandemi Covid-19 yang dimulai sejak awal tahun 2020 dapat menjadi penyebab kecemasan pada ibu hamil sehingga dapat mengurangi kualitas kehamilan. Menurut survei pendahuluan yang dilakukan di wilayah kelurahan Dodu Kota Bima, 70% ibu hamil mengalami kecemasan oleh karena tidak bisa melakukan pemeriksaan secara rutin di pelayanan kesehatan. Tujuan dari penelitian ini adalah untuk mengetahui pengaruh edukasi Family Centered Maternity Care (FCMC) menggunakan Whatsapp dan booklet terhadap kecemasan ibu hamil pada masa pandemi Covid-19 Di Kelurahan Dodu Kota Bima.

 

Desain penelitian menggunakan pendekatan quasi experiment dengan rancangan pre test-pos test kontrol group design. Populasi dalam penelitian ini seluruh Ibu hamil di Kelurahan Dodu Kota Bima. Pengambilan sampel dalam penelitian ini menggunakan teknik total sampling dengan jumlah sampel 34 responden. Instrumen penelitian ini menggunakan HP Andorid untuk WhatsApp, booklet, dan Kuesioner HARS.

 

Sebelum perlakuan, kecemasan ibu hamil pada kelompok control (94%) dan perlakuan (82%) sebagian besar memiliki tingkat cemas berat. Sebelum dan sesudah perlakuan, semua  ibu hamil mengalami kecemasan. Hal itu wajar karena kehamilan akan mengakibatkan kecemasan tersendiri. Yang membedakan adalah tingkatannya. Sesudah perlakuan, tingkat kecemasan ibu hamil mengalami penurunan.

 

Ada pengaruh edukasi FCMC menggunakan whatsapp dan booklet terhadap kecemasan ibu hamil pada masa pandemi Covid-19 di kelurahan Dodu Kota Bima (p=0.000). Penggunaan whatsaap lebih besar pengaruhnya menurunkan kecemasan ibu hamil. Diharapkan program pemerintah di Kota Bima yang akan datang dapat menggunakan metode ini untuk mengedukasi ibu hamil dalam bidang kesehatan ibu dan anak.

 

Kata kunci: Covid-19, edukasi, ibu hamil, WhatsApp, booklet
Birch pollen—The unpleasant herald of spring
Authors: Raith Marianne , Swoboda Ines
Published: May 2023

Type I respiratory allergies to birch pollen and pollen from related trees of the order Fagales are increasing in industrialized countries, especially in the temperate zone of the Northern hemisphere, but the reasons for this increase are still debated and seem to be multifaceted. While the most important allergenic molecules of birch pollen have been identified and characterized, the contribution of other pollen components, such as lipids, non-allergenic immunomodulatory proteins, or the pollen microbiome, to the development of allergic reactions are sparsely known. Furthermore, what also needs to be considered is that pollen is exposed to external influences which can alter its allergenicity. These external influences include environmental factors such as gaseous pollutants like ozone or nitrogen oxides or particulate air pollutants, but also meteorological events like changes in temperature, humidity, or precipitation. In this review, we look at the birch pollen from different angles and summarize current knowledge on internal and external influences that have an impact on the allergenicity of birch pollen and its interactions with the epithelial barrier. We focus on epithelial cells since these cells are the first line of defense in respiratory disease and are increasingly considered to be a regulatory tissue for the protection against the development of respiratory allergies.
Gene representation in scRNA-seq is correlated with common motifs at the 3′ end of transcripts
Authors: Li Xinling , Gibson Greg , Qiu Peng
Published: May 2023

One important characteristic of single-cell RNA sequencing (scRNA-seq) data is its high sparsity, where the gene-cell count data matrix contains high proportion of zeros. The sparsity has motivated widespread discussions on dropouts and missing data, as well as imputation algorithms of scRNA-seq analysis. Here, we aim to investigate whether there exist genes that are more prone to be under-detected in scRNA-seq, and if yes, what commonalities those genes may share. From public data sources, we gathered paired bulk RNA-seq and scRNA-seq data from 53 human samples, which were generated in diverse biological contexts. We derived pseudo-bulk gene expression by averaging the scRNA-seq data across cells. Comparisons of the paired bulk and pseudo-bulk gene expression profiles revealed that there indeed exists a collection of genes that are frequently under-detected in scRNA-seq compared to bulk RNA-seq. This result was robust to randomization when unpaired bulk and pseudo-bulk gene expression profiles were compared. We performed motif search to the last 350 bp of the identified genes, and observed an enrichment of poly(T) motif. The poly(T) motif toward the tails of those genes may be able to form hairpin structures with the poly(A) tails of their mRNA transcripts, making it difficult for their mRNA transcripts to be captured during scRNA-seq library preparation, which is a mechanistic conjecture of why certain genes may be more prone to be under-detected in scRNA-seq.
Pre-epithelialized cryopreserved tracheal allograft for neo-trachea flap engineering
Authors: Zeng Ning , Chen Youbai , Wu Yewen , Zang Mengqing , Largo Rene D. , Chang Edward I. , Schaverien Mark V. , Yu Peirong , Zhang Qixu
Published: May 2023

Graphical Abstract

Scheme of the experimental design. 1, CTA derived from donor Brown Norway rats was de-epithelialized to create DeCTA. 2, RECs were isolated from syngeneic recipient Lewis rats. 3, DeCTA was pre-epithelialized to create ReCTA. 4, In the heterotopic implantation model, ReCTA was subcutaneously implanted into the groin area, and an adipose tissue flap pedicled by superficial epigastric blood vessels was used for neovascularization. 5, In the orthotopic implantation model, DeCTA was implanted into the neck to reconstruct a 4-ring tracheal defect.
A bibliometric analysis of artificial intelligence applications in macular edema: exploring research hotspots and Frontiers
Authors: Feng Haiwen , Chen Jiaqi , Zhang Zhichang , Lou Yan , Zhang Shaochong , Yang Weihua
Published: May 2023

Background: Artificial intelligence (AI) is used in ophthalmological disease screening and diagnostics, medical image diagnostics, and predicting late-disease progression rates. We reviewed all AI publications associated with macular edema (ME) research Between 2011 and 2022 and performed modeling, quantitative, and qualitative investigations.

Methods: On 1st February 2023, we screened the Web of Science Core Collection for AI applications related to ME, from which 297 studies were identified and analyzed (2011–2022). We collected information on: publications, institutions, country/region, keywords, journal name, references, and research hotspots. Literature clustering networks and Frontier knowledge bases were investigated using bibliometrix-BiblioShiny, VOSviewer, and CiteSpace bibliometric platforms. We used the R “bibliometrix” package to synopsize our observations, enumerate keywords, visualize collaboration networks between countries/regions, and generate a topic trends plot. VOSviewer was used to examine cooperation between institutions and identify citation relationships between journals. We used CiteSpace to identify clustering keywords over the timeline and identify keywords with the strongest citation bursts.

Results: In total, 47 countries published AI studies related to ME; the United States had the highest H-index, thus the greatest influence. China and the United States cooperated most closely between all countries. Also, 613 institutions generated publications - the Medical University of Vienna had the highest number of studies. This publication record and H-index meant the university was the most influential in the ME field. Reference clusters were also categorized into 10 headings: retinal Optical Coherence Tomography (OCT) fluid detection, convolutional network models, deep learning (DL)-based single-shot predictions, retinal vascular disease, diabetic retinopathy (DR), convolutional neural networks (CNNs), automated macular pathology diagnosis, dry age-related macular degeneration (DARMD), class weight, and advanced DL architecture systems. Frontier keywords were represented by diabetic macular edema (DME) (2021–2022).

Conclusion: Our review of the AI-related ME literature was comprehensive, systematic, and objective, and identified future trends and current hotspots. With increased DL outputs, the ME research focus has gradually shifted from manual ME examinations to automatic ME detection and associated symptoms. In this review, we present a comprehensive and dynamic overview of AI in ME and identify future research areas.
Hybrid modeling for biopharmaceutical processes: advantages, opportunities, and implementation
Authors: Narayanan Harini , von Stosch Moritz , Feidl Fabian , Sokolov Michael , Morbidelli Massimo , Butté Alessandro
Published: May 2023

Process models are mathematical formulations (essentially a set of equations) that try to represent the real system/process in a digital or virtual form. These are derived either based on fundamental physical laws often combined with empirical assumptions or learned based on data. The former has been existing for several decades in chemical and process engineering while the latter has recently received a lot of attention with the emergence of several artificial intelligence/machine learning techniques. Hybrid modeling is an emerging modeling paradigm that explores the synergy between existing these two paradigms, taking advantage of the existing process knowledge (or engineering know-how) and information disseminated by the collected data. Such an approach is especially suitable for systems and industries where data generation is significantly resource intensive while at the same time fundamentally not completely deciphered such as the processes involved in the biopharmaceutical pipeline. This technology could, in fact, be the enabler to meeting the demands and goals of several initiatives such as Quality by design, Process Analytical tools, and Pharma 4.0. In addition, it can aid in different process applications throughout process development and Chemistry, Manufacturing, and Control (CMC) to make it more strategic and efficient. This article focuses on providing a step-by-step guide to the different considerations to be made to develop a reliable and applicable hybrid model. In addition, the article aims at highlighting the need for such tools in the biopharmaceutical industry and summarizes the works that advocate its implications. Subsequently, the key qualities of hybrid modeling that make it a key enabler in the biopharmaceutical industry are elaborated with reference to the literature demonstrating such qualities.
Hospital and community wastewater as a source of multidrug-resistant ESBL-producing Escherichia coli
Authors: Davidova-Gerzova Lenka , Lausova Jarmila , Sukkar Iva , Nesporova Kristina , Nechutna Lucie , Vlkova Katerina , Chudejova Katerina , Krutova Marcela , Palkovicova Jana , Kaspar Jakub , Dolejska Monika
Published: May 2023

Introduction

Hospitals and wastewater are recognized hot spots for the selection and dissemination of antibiotic-resistant bacteria to the environment, but the total participation of hospitals in the spread of nosocomial pathogens to municipal wastewater treatment plants (WWTPs) and adjacent rivers had not previously been revealed.

Methods

We used a combination of culturing and whole-genome sequencing to explore the transmission routes of Escherichia coli from hospitalized patients suffering from urinary tract infections (UTI) via wastewater to the environment. Samples were collected in two periods in three locations (A, B, and C) and cultured on selective antibiotic-enhanced plates.

Results

In total, 408 E. coli isolates were obtained from patients with UTI (n=81), raw hospital sewage (n=73), WWTPs inflow (n=96)/outflow (n=106), and river upstream (n=21)/downstream (n=31) of WWTPs. The majority of the isolates produced extended-spectrum beta-lactamase (ESBL), mainly CTX-M-15, and showed multidrug resistance (MDR) profiles. Seven carbapenemase-producing isolates with GES-5 or OXA-244 were obtained in two locations from wastewater and river samples. Isolates were assigned to 74 different sequence types (ST), with the predominance of ST131 (n=80) found in all sources including rivers. Extraintestinal pathogenic lineages frequently found in hospital sewage (ST10, ST38, and ST69) were also found in river water. Despite generally high genetic diversity, phylogenetic analysis of ST10, ST295, and ST744 showed highly related isolates (SNP 0-18) from different sources, providing the evidence for the transmission of resistant strains through WWTPs to surface waters.

Discussion

Results of this study suggest that 1) UTI share a minor participation in hospitals wastewaters; 2) a high diversity of STs and phylogenetic groups in municipal wastewaters derive from the urban influence rather than hospitals; and 3) pathogenic lineages and bacteria with emerging resistance genotypes associated with hospitals spread into surface waters. Our study highlights the contribution of hospital and municipal wastewater to the transmission of ESBL- and carbapenemase-producing E. coli with MDR profiles to the environment.
Effectiveness of regdanvimab treatment for SARS-CoV-2 delta variant, which exhibited decreased in vitro activity: a nationwide real-world multicenter cohort study
Authors: Kim Haein , Jang Young Rock , Lee Ji Yeon , Ko Jae-Hoon , Lee Jee Young , Cho Seongcheol , Lee Yong Dae , Song Junghoon , Hyun Miri , Kim Hyun Ah , Hwang Soyoon , Ryou Sangmi , Na Yoo Jin , Lee Joo-Yeon , Lee Changhee , Lee Nan Young , Shin Seunghwan , Kwon Ki Tae , Kim Jin Yong , Peck Kyong Ran
Published: May 2023

Background

Immune-evading severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants are emerging continuously. The clinical effectiveness of monoclonal antibody agents that exhibit decreased in vitro activity against SARS-CoV-2 variants needs to be elucidated.

Methods

A nationwide, multicenter, retrospective cohort study was designed to evaluate the effectiveness of regdanvimab, an anti-SARS-CoV-2 monoclonal antibody agent. Regdanvimab was prescribed in South Korea before and after the emergence of the delta variant, against which the in vitro activity of regdanvimab was decreased but present. Mild to moderate coronavirus 2019 (COVID-19) patients with risk factors for disease progression who were admitted within seven days of symptom onset were screened in four designated hospitals between December 2020 and September 2021. The primary outcomes, O2 requirements and progression to severe disease within 21 days of admission, were compared between the regdanvimab and supportive care groups, with a subgroup analysis of delta variant–confirmed patients.

Results

A total of 2,214 mild to moderate COVID-19 patients were included, of whom 1,095 (49.5%) received regdanvimab treatment. In the analysis of the total cohort, significantly fewer patients in the regdanvimab group than the supportive care group required O2 support (18.4% vs. 27.1%, P < 0.001) and progressed to severe disease (4.0% vs. 8.0%, P < 0.001). In the multivariable analysis, regdanvimab was significantly associated with a decreased risk for O2 support (HR 0.677, 95% CI 0.561–0.816) and progression to severe disease (HR 0.489, 95% CI 0.337–0.709). Among the 939 delta-confirmed patients, O2 support (21.5% vs. 23.5%, P = 0.526) and progression to severe disease (4.2% vs. 7.3%, P = 0.055) did not differ significantly between the regdanvimab and supportive care groups. In the multivariable analyses, regdanvimab treatment was not significantly associated with a decreased risk for O2 support (HR 0.963, 95% CI 0.697–1.329) or progression to severe disease (HR 0.665, 95% CI 0.349–1.268) in delta-confirmed group.

Conclusions

Regdanvimab treatment effectively reduced progression to severe disease in the overall study population, but did not show significant effectiveness in the delta-confirmed patients. The effectiveness of dose increment of monoclonal antibody agents should be evaluated for variant strains exhibiting reduced susceptibility.
A model of an accessibility curriculum in higher education
Authors: Weeden Elissa
Published: May 2023

Individuals may face daily unnecessary challenges and barriers in digital and physical spaces and in the use of products, which can result in exclusion. As a society, we need to do better regarding accessibility. One step toward removing challenges and barriers to a more accessible and inclusive society is to increase awareness and knowledge around accessibility. Toward that end, a 4-year private technical university in the northeast United States has offered a four-course curriculum dedicated to accessibility. This curriculum, instruction, and pedagogy paper will describe the design and delivery of the four-course accessibility curriculum consisting of Design for Accessibility, Access and Assistive Technology, Accessibility Through the Lifespan, and Research in Accessibility. This model curriculum aims to educate students to mindfully consider, advocate, and increase accessibility as they prepare to enter the workforce to create digital and physical spaces and products.
Association between MetS-IR and prediabetes risk and sex differences: a cohort study based on the Chinese population
Authors: Xie Qiyang , Kuang Maobin , Lu Song , Huang Xin , Wang Chao , Zhang Shuhua , Sheng Guotai , Zou Yang
Published: May 2023

Objective

The metabolic score for insulin resistance (MetS-IR) is an emerging surrogate marker for insulin resistance (IR). This study aimed to investigate the association and sex differences between MetS-IR and prediabetes risk in a Chinese population.

Methods

This cohort study included 100,309 adults with normoglycemia at baseline and had followed longitudinally for 5 years, and with prediabetes, defined according to the 2018 American Diabetes Association (ADA) recommended diagnostic criteria, as the outcome of interest. Multivariate Cox proportional hazards regression and restricted cubic spline (RCS) regression models were used to assess the association between MetS-IR and prediabetes risk.

Results

During an observation period of 312,843 person-years, 7,735 (14.84%) men and 4,617 (9.57%) women with pre-diabetes onset were recorded. After fully adjusting for confounders, we found an independent and positive correlation between MetS-IR and the risk of prediabetes in the Chinese population, and the degree of correlation was stronger in women than in men (HR: 1.24 vs 1.16, P-interaction<0.05). Furthermore, using RCS nested in the Cox regression model, we found that there was a nonlinear correlation between MetS-IR and prediabetes risk in both sexes with an obvious saturation effect point, and when the MetS-IR was greater than the value of the saturation effect point, the risk of prediabetes was gradually leveling off. We further calculated the saturation effect points of MetS-IR used to evaluate the risk of prediabetes which in men was 42.82, and in women was 41.78.

Conclusion

In this large cohort study, our results supported that MetS-IR was independently and positively associated with the risk of prediabetes in the Chinese population, with the association being stronger in women than in men.
The current trends of bioethanol production from cheese whey using yeasts: biological and economical perspectives
Authors: Tesfaw Asmamaw
Published: May 2023

Besides organic compounds such as lactose and proteins, cheese whey is rich in other nutrients. Damping of these valuable compounds to the environment, first, harms the environment, and second, it wastes valuable resources. Therefore, this review aims to find out the current progress on the valorization of cheese whey for ethanol production. Efficient ethanol-producing yeasts like Saccharomyces cerevisiae have no pathway to utilize lactose and, therefore, they can be co-cultured with microbes that can produce β-galactosidase. In addition, chemical, biological, and physical hydrolysis of lactose can be used to produce ethanol from cheese whey. Ethanol production from unsterilized or unpasteurized whey is very promising and this reduces the production cost significantly. This suggests that the ethanol-producing yeasts are competent against the lactic acid bacteria that are commonly found in cheese whey. Despite the presence of central metabolic genes associated with ethanol production from different sugars in some yeasts, these yeasts can’t ferment the different sugars and this is basically due to a lack of the different sugar transport systems in the yeasts. Therefore, additions of different sugars to whey to increase the sugar content for economical ethanol production are impaired by catabolite repressions. However, catabolite repression can be significantly reduced by metabolic engineering by targeting sugar transporter proteins like the major facilitator superfamily (MFS), particularly LAC, CEL2, HGT, RAG, and KHT. Therefore, this enhances ethanol production from cheese whey supplemented with a variety of sugars. Currently, nanoparticles and metal-organic frameworks coated immobilization of S. cerevisiae produced higher ethanol from lignocellulosic substrates than the classical carries such as alginates; however, studies of such immobilizing materials on Kluveromyces spp for ethanol production are very limited, and open for research. Electro-fermentation, an emerging bioprocess to control microbial fermentative metabolism, boosts ethanol production, enables the production of 14% (v/v) ethanol, and shortens the fermentation time of high sugar-containing whey. Generally, utilizing efficient yeast (possibly by adaptive evolution and genetic engineering) at optimal fermenting conditions enabled to production of economical ethanol from cheese whey that contains higher sugars (greater than 15%) at the large-scale cheese processing industries.
Evaluating the use of statistical and machine learning methods for estimating breed composition of purebred and crossbred animals in thirteen cattle breeds using genomic information
Authors: Ryan C. A. , Berry D. P. , O’Brien A. , Pabiou T. , Purfield D. C.
Published: May 2023

Introduction: The ability to accurately predict breed composition using genomic information has many potential uses including increasing the accuracy of genetic evaluations, optimising mating plans and as a parameter for genotype quality control. The objective of the present study was to use a database of genotyped purebred and crossbred cattle to compare breed composition predictions using a freely available software, Admixture, with those from a single nucleotide polymorphism Best Linear Unbiased Prediction (SNP-BLUP) approach; a supplementary objective was to determine the accuracy and general robustness of low-density genotype panels for predicting breed composition.

Methods: All animals had genotype information on 49,213 autosomal single nucleotide polymorphism (SNPs). Thirteen breeds were included in the analysis and 500 purebred animals per breed were used to establish the breed training populations. Accuracy of breed composition prediction was determined using a separate validation population of 3,146 verified purebred and 4,330 two and three-way crossbred cattle.

Results: When all 49,213 autosomal SNPs were used for breed prediction, a minimal absolute mean difference of 0.04 between Admixture vs. SNP-BLUP breed predictions was evident. For crossbreds, the average absolute difference in breed prediction estimates generated using SNP-BLUP and Admixture was 0.068 with a root mean square error of 0.08. Breed predictions from low-density SNP panels were generated using both SNP-BLUP and Admixture and compared to breed prediction estimates using all 49,213 SNPs (representing the gold standard). Breed composition estimates of crossbreds required more SNPs than predicting the breed composition of purebreds. SNP-BLUP required ≥3,000 SNPs to predict crossbred breed composition, but only 2,000 SNPs were required to predict purebred breed status. The absolute mean (standard deviation) difference across all panels <2,000 SNPs was 0.091 (0.054) and 0.315 (0.316) when predicting the breed composition of all animals using Admixture and SNP-BLUP, respectively compared to the gold standard prediction.

Discussion: Nevertheless, a negligible absolute mean (standard deviation) difference of 0.009 (0.123) in breed prediction existed between SNP-BLUP and Admixture once ≥3,000 SNPs were considered, indicating that the prediction of breed composition could be readily integrated into SNP-BLUP pipelines used for genomic evaluations thereby avoiding the necessity for a stand-alone software.
New molecular targets in Hodgkin and Reed-Sternberg cells
Authors: Sadaf Hummaira , Ambroziak Maciej , Binkowski Robert , Kluebsoongnoen Jakkapong , Paszkiewicz-Kozik Ewa , Steciuk Jaroslaw , Markowicz Sergiusz , Walewski Jan , Sarnowska Elzbieta , Sarnowski Tomasz Jacek , Konopinski Ryszard
Published: May 2023

Recent discoveries shed light on molecular mechanisms responsible for classical Hodgkin lymphoma (HL) development and progression, along with features of Hodgkin – Reed and Sternberg cells (HRS). Here, we summarize current knowledge on characteristic molecular alterations in HL, as well as existing targeted therapies and potential novel treatments for this disease. We discuss the importance of cluster of differentiation molecule 30 (CD30) and the programmed cell death-1 protein (PD-1) and ligands (PD-L1/2), and other molecules involved in immune modulation in HL. We highlight emerging evidence indicating that the altered function of SWI/SNF-type chromatin remodeling complexes, PRC2, and other epigenetic modifiers, contribute to variations in chromatin status, which are typical for HL. We postulate that despite of the existence of plentiful molecular data, the understanding of HL development remains incomplete. We therefore propose research directions involving analysis of reverse signaling in the PD-1/PD-L1 mechanism, chromatin remodeling, and epigenetics-related alterations, in order to identify HL features at the molecular level. Such attempts may lead to the identification of new molecular targets, and thus will likely substantially contribute to the future development of more effective targeted therapies.
Serum immune mediators as novel predictors of response to anti-PD-1/PD-L1 therapy in non-small cell lung cancer patients with high tissue-PD-L1 expression
Authors: Raza Afsheen , Mohsen Reyad , Kanbour Aladdin , Zar Gul Abdul Rehman , Philip Anite , Vijayakumar Suma , Hydrose Shereena , Prabhu Kirti S. , Al-Suwaidi Aisha Khamis , Inchakalody Varghese Philipose , Merhi Maysaloun , Abo El-Ella Dina M. , Tauro Melissa Annrose , Akbar Shayista , Al-Bozom Issam , Abualainin Wafa , Al-Abdulla Rajaa , Sirriya Shaza Abu , Hassnad Suparna , Uddin Shahab , Mohamed Ibrahim Mohamed Izham , Al Homsi Ussama , Demime Said
Published: May 2023

Background

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related morbidity and mortality worldwide. Immune checkpoint inhibitors (ICIs) including anti-PD-1 and anti-PD-L1 antibodies, have significantly changed the treatment outcomes with better overall survival, but only 15-40% of the patients respond to ICIs therapy. The search for predictive biomarkers of responses is warranted for better clinical outcomes. We aim here to identify pre-treatment soluble immune molecules as surrogate biomarkers for tissue PD-L1 (TPD-L1) status and as predictors of response to anti-PD-1/PD-L1 therapy in NSCLC patients. Sera from 31 metastatic NSCLC patients, eligible for anti-PD-1/PD-L1 or combined chemoimmunotherapy, were collected prior to treatment. Analysis of soluble biomarkers with TPD-L1 status showed significant up/down regulation of the immune inhibitory checkpoint markers (sSiglec7, sSiglec9, sULBP4 and sPD-L2) in patients with higher TPD-L1 (TPD-L1 >50%) expression. Moreover, correlation analysis showed significant positive linear correlation of soluble PD-L1 (sPD-L1) with higher TPD-L1 expression. Interestingly, only responders in the TPD-L1 >50% group showed significant down regulation of the immune inhibitory markers (sPD-L2, sTIMD4, sNectin2 and CEA). When responders vs. non-responders were compared, significant down regulation of other immune inhibitory biomarkers (sCD80, sTIMD4 and CEA) was recorded only in responding patients. In this, the optimal cut-off values of CD80 <91.7 pg/ml and CEA <1614 pg/ml were found to be significantly associated with better progression free survival (PFS). Indeed, multivariate analysis identified the cutoff-value of CEA <1614 pg/ml as an independent predictor of response in our patients. We identified here novel immune inhibitory/stimulatory soluble mediators as potential surrogate/predictive biomarkers for TPD-L1 status, treatment response and PFS in NSCLC patients treated with anti-PD-1/PD-L1 therapy.
From bench to bedside: the history and progress of CAR T cell therapy
Authors: Mitra Aroshi , Barua Amrita , Huang Luping , Ganguly Siddhartha , Feng Qin , He Bin
Published: May 2023

Chimeric antigen receptor (CAR) T cell therapy represents a major breakthrough in cancer care since the approval of tisagenlecleucel by the Food and Drug Administration in 2017 for the treatment of pediatric and young adult patients with relapsed or refractory acute lymphocytic leukemia. As of April 2023, six CAR T cell therapies have been approved, demonstrating unprecedented efficacy in patients with B-cell malignancies and multiple myeloma. However, adverse events such as cytokine release syndrome and immune effector cell-associated neurotoxicity pose significant challenges to CAR T cell therapy. The severity of these adverse events correlates with the pretreatment tumor burden, where a higher tumor burden results in more severe consequences. This observation is supported by the application of CD19-targeted CAR T cell therapy in autoimmune diseases including systemic lupus erythematosus and antisynthetase syndrome. These results indicate that initiating CAR T cell therapy early at low tumor burden or using debulking strategy prior to CAR T cell infusion may reduce the severity of adverse events. In addition, CAR T cell therapy is expensive and has limited effectiveness against solid tumors. In this article, we review the critical steps that led to this groundbreaking therapy and explore ongoing efforts to overcome these challenges. With the promise of more effective and safer CAR T cell therapies in development, we are optimistic that a broader range of cancer patients will benefit from this revolutionary therapy in the foreseeable future.
Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins
Authors: Pan Sai , Zhao Wenting , Li Yizhan , Ying Zhijun , Luo Yihong , Wang Qinchuan , Li Xiawei , Lu Wenjie , Dong Xin , Wu Yulian , Wu Xifeng
Published: May 2023

Background

Immune checkpoint inhibition holds promise as a novel treatment for pancreatic ductal adenocarcinoma (PDAC). The clinical significance of soluble immune checkpoint (ICK) related proteins have not yet fully explored in PDAC.

Methods

We comprehensively profiled 14 soluble ICK-related proteins in plasma in 70 PDAC patients and 70 matched healthy controls. Epidemiological data of all subjects were obtained through structured interviews, and patients’ clinical data were retrieved from electronical health records. We evaluated the associations between the biomarkers with the risk of PDAC using unconditional multivariate logistic regression. Consensus clustering (k-means algorithm) with significant biomarkers was performed to identify immune subtypes in PDAC patients. Prediction models for overall survival (OS) in PDAC patients were developed using multivariate Cox proportional hazards regression. Harrell’s concordance index (C-index), time-dependent receiver operating characteristic (ROC) curve and calibration curve were utilized to evaluate performance of prediction models. Gene expressions of the identified ICK-related proteins in tumors from TCGA were analyzed to provide insight into underlying mechanisms.

Results

Soluble BTLA, CD28, CD137, GITR and LAG-3 were significantly upregulated in PDAC patients (all q < 0.05), and elevation of each of them was correlated with PDAC increased risk (all p < 0.05). PDAC patients were classified into soluble immune-high and soluble immune-low subtypes, using these 5 biomarkers. Patients in soluble immune-high subtype had significantly poorer OS than those in soluble immune-low subtype (log-rank p = 9.7E-03). The model with clinical variables and soluble immune subtypes had excellent predictive power (C-index = 0.809) for the OS of PDAC patients. Furthermore, the immune subtypes identified with corresponding genes’ expression in PDAC tumor samples in TCGA showed an opposite correlation with OS to that of immune subtypes based on blood soluble ICK-related proteins (log-rank p =0.02). The immune-high subtype tumors displayed higher cytolytic activity (CYT) score than immune-low subtype tumors (p < 2E-16).

Conclusion

Five soluble ICK-related proteins were identified to be significantly associated with the risk and prognosis of PDAC. Patients who were classified as soluble immune-low subtype based on these biomarkers had better overall survival than those of the soluble immune-high subtype.
The fusiform gyrus exhibits differential gene-gene co-expression in Alzheimer's disease
Authors: Ribeiro-dos-Santos Arthur , de Brito Leonardo Miranda , de Araújo Gilderlanio Santana
Published: May 2023

Alzheimer's Disease (AD) is an irreversible neurodegenerative disease clinically characterized by the presence of β-amyloid plaques and tau deposits in various regions of the brain. However, the underlying factors that contribute to the development of AD remain unclear. Recently, the fusiform gyrus has been identified as a critical brain region associated with mild cognitive impairment, which may increase the risk of AD development. In our study, we performed gene co-expression and differential co-expression network analyses, as well as gene-expression-based prediction, using RNA-seq transcriptome data from post-mortem fusiform gyrus tissue samples collected from both cognitively healthy individuals and those with AD. We accessed differential co-expression networks in large cohorts such as ROSMAP, MSBB, and Mayo, and conducted over-representation analyses of gene pathways and gene ontology. Our results comprise four exclusive gene hubs in co-expression modules of Alzheimer's Disease, including FNDC3A, MED23, NRIP1, and PKN2. Further, we identified three genes with differential co-expressed links, namely FAM153B, CYP2C8, and CKMT1B. The differential co-expressed network showed moderate predictive performance for AD, with an area under the curve ranging from 0.71 to 0.76 (+/− 0.07). The over-representation analysis identified enrichment for Toll-Like Receptors Cascades and signaling pathways, such as G protein events, PIP2 hydrolysis and EPH-Epherin mechanism, in the fusiform gyrus. In conclusion, our findings shed new light on the molecular pathophysiology of AD by identifying new genes and biological pathways involved, emphasizing the crucial role of gene regulatory networks in the fusiform gyrus.
Automated detection of hippocampal sclerosis using real-world clinical MRI images
Authors: Jiang Jingwen , Qiu Jiajun , Yin Jin , Wang Junren , Jiang Xinyue , Yi Zuo , Chen Yang , Zhou Xiaobo , Sima Xiutian
Published: May 2023

Background

Hippocampal sclerosis (HS) is the most common pathological type of temporal lobe epilepsy (TLE) and one of the important surgical markers. Currently, HS is mainly diagnosed manually by radiologists based on visual inspection of MRI, which greatly relies on MRI quality and physician experience. In clinical practice, non-thin MRI scans are often used due to the time and efficiency needed for the acquisition. However, these scans can be difficult for junior physicians to interpret accurately. Thus, the rapid and accurate diagnosis of HS using real-world MRI images in clinical settings is a challenging task.

Objective

Our aim was to explore the feasibility of using computer vision methods to diagnose HS on real-world clinical MRI images and to provide a reference for future clinical applications of artificial intelligence methods to aid in detecting HS.

Methods

We proposed a deep learning algorithm called “HS-Net” to discriminate HS using real-world clinical MRI images. First, we delineated and segmented a region of interest (ROI) around the hippocampus. Then, we utilized the fractional differential (FD) method to enhance the textures of the ROIs. Finally, we used a small-sample image classification method based on transfer learning to fine-tune the feature extraction part of a pretrained model and added two fully connected layers and an output layer. In the study, 96 TLE patients with HS confirmed by postoperative pathology and 89 healthy controls were retrospectively enrolled. All subjects were cross-validated, and models were evaluated for performance, robustness, and clinical utility.

Results

The HS-Net model achieved an area under the curve (AUC) of 0.894, an accuracy of 82.88%, an F1-score of 84.08% in the test cohort based on real, routine, clinical T2-weighted fluid attenuated inversion recovery (FLAIR) sequence MRI images. Additionally, the AUC, accuracy and F1 scores of our model all increased by around 3 percentage points when the inputs were augmented with the ROIs of the textures enhanced using the FD method.

Conclusions

Our computational model has the potential to be used for the diagnosis of HS in real clinical MRI images, which could assist physicians, particularly junior physicians, in improving the accuracy of discrimination.
γ-Aminobutyric acid as a biomarker of the lateralizing and monitoring drug effect in patients with magnetic resonance imaging-negative temporal lobe epilepsy
Authors: Wu Shuohua , Wang Qianqi , Zhai Huige , Zhang Yiwen , Xu Dongyuan , Yan Gen , Wu Renhua
Published: May 2023

Introduction

Despite verifying proton magnetic resonance spectroscopy (1H-MRS) for focal localization in magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE), it is necessary to illustrate metabolic changes and screen for effective biomarkers for monitoring therapeutic effect. We used 1H-MRS to investigate the role of metabolic levels in MRI-negative TLE.

Materials and methods

Thirty-seven patients (n = 37, 14 women) and 20 healthy controls (n = 20, 11 women) were investigated by 1H-MRS. We compared the metabolite level changes in the epileptic and contralateral sides on the mesial temporal and dorsolateral prefrontal cortices and analyzed their association with clinical symptoms.

Results

γ-Aminobutyric acid (GABA) levels were significantly lower on the epileptic side (2.292 ± 0.890) than in the contralateral side (2.662 ± 0.742, p = 0.029*) in patients on the mesial temporal lobe. N-acetylaspartate (NAA) levels were significantly lower on the epileptic side (7.284 ± 1.314) than on the contralateral side (7.655 ± 1.549, p = 0.034*). NAA + N-acetylaspartylglutamate levels were significantly lower on the epileptic side (7.668 ± 1.406) than on the contralateral side (8.086 ± 1.675, p = 0.032*). Glutamate levels were significantly lower on the epileptic side (7.773 ± 1.428) than on the contralateral side (8.245 ± 1.616, p = 0.040*). Moreover, a significant negative correlation was found between GABA levels in the epileptic mesial temporal lobe and tonic–clonic seizure frequency (r = −0.338, p = 0.046*).

Conclusion

γ-Aminobutyric acid (GABA) is a potential biomarker for lateralization and monitoring seizure frequency in MRI-negative TLE.
Calorie restriction and pravastatin administration during pregnancy in obese rhesus macaques modulates maternal and infant metabolism and infant brain and behavioral development
Authors: Hasegawa Yu , Kim Danielle H. J. , Zhang Zhichao , Taha Ameer Y. , Capitanio John P. , Hogrefe Casey E. , Bauman Melissa D. , Golub Mari S. , Van de Water Judy , VandeVoort Catherine A. , Walker Cheryl K. , Slupsky Carolyn M.
Published: May 2023

Background

Maternal obesity has been associated with a higher risk of pregnancy-related complications in mothers and offspring; however, effective interventions have not yet been developed. We tested two interventions, calorie restriction and pravastatin administration, during pregnancy in a rhesus macaque model with the hypothesis that these interventions would normalize metabolic dysregulation in pregnant mothers leading to an improvement in infant metabolic and cognitive/social development.

Methods

A total of 19 obese mothers were assigned to either one of the two intervention groups (n = 5 for calorie restriction;n = 7 for pravastatin) or an obese control group (n = 7) with no intervention, and maternal gestational samples and postnatal infant samples were compared with lean control mothers (n = 6) using metabolomics methods.

Results

Gestational calorie restriction normalized one-carbon metabolism dysregulation in obese mothers, but altered energy metabolism in her offspring. Although administration of pravastatin during pregnancy tended to normalize blood cholesterol in the mothers, it potentially impacted the gut microbiome and kidney function of their offspring. In the offspring, both calorie restriction and pravastatin administration during pregnancy tended to normalize the activity of AMPK in the brain at 6 months, and while results of the Visual Paired-Comparison test, which measures infant recognition memory, was not significantly impacted by either of the interventions, gestational pravastatin administration, but not calorie restriction, tended to normalize anxiety assessed by the Human Intruder test.

Conclusions

Although the two interventions tested in a non-human primate model led to some improvements in metabolism and/or infant brain development, negative impacts were also found in both mothers and infants. Our study emphasizes the importance of assessing gestational interventions for maternal obesity on both maternal and offspring long-term outcomes.
Potential of macronutrients and probiotics to boost immunity in patients with SARS-COV-2: a narrative review
Authors: Mardi Afrouz , Kamran Aziz , Pourfarzi Farhad , Zare Maryam , Hajipour Azadeh , Doaei Saeid , Abediasl Negin , Hackett Daniel
Published: May 2023

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-COV-2) may cause inflammation and increased cytokine secretion. Dietary factors may play an important role in enhancing the immune responses against infectious diseases such as SARS-COV-2. This narrative review aims to determine the effectiveness of macronutrients and probiotics to improve immunity in SARS-COV-2 patients. Dietary proteins may boost pulmonary function in SARS-COV-2 patients through inhibitory effects on the Angiotensin-converting enzyme (ACE) and reduce Angiotensin (ANG-II). Moreover, omega-3 fatty acids may improve oxygenation, acidosis, and renal function. Dietary fiber may also produce anti-inflammatory effects by reducing the level of high-sensitivity C-Reactive Protein (hs-CRP), Interleukin (IL-6), and Tumor necrosis factor (TNF-α). In addition, some evidence indicates that probiotics significantly improve oxygen saturation which may enhance survival rate. In conclusion, the consumption of a healthy diet including adequate macronutrients and probiotic intake may decrease inflammation and oxidative stress. Following this dietary practice is likely to strengthen the immune system and have beneficial effects against SARS-COV-2.