bluuebunny/crossref_metadata_2025 huggingface dataset:
The Relationship Between Arm Muscle Explosiveness And Hand-Eye Coordination With Top Service Accuracy in Volleyball Extracurricular Activities Female Student at SMA Negeri 1 Tembilahan Hulu
Authors: Mardiah Ainul , Antoni Prima , Wilastra Devit
Published: September 2023

This type of research is correlational. This study aims to determine the relationship between Arm Muscle Explosiveness and Hand Eye Coordination with Upper Service Accuracy in Sawa Putri Volleyball Extracurricular Activities at SMA Negeri 1 Tembilahan Hulu. The population in this study amounted to 15 people. The sample in this study used total sampling, which consisted of 15 female students. The instruments used in this study were the Two-Hand Medicine Ball Putt test for the Arm Muscle Explosive Power, the Ballwerfen und-Fangen test for eye-hand coordination and the target field for the upper serve test. The results of this study concluded that there was a significant relationship between the explosive power of the arm muscles and the accuracy of serving in volleyball rcount = 0.72 > 0.514. And there is a significant relationship between hand eye coordination and accuracy of serving volleyball rcount = 0.86 > 0.514 and there is also a significant relationship between the explosive power of the arm muscles and hand eye coordination with accuracy of serving volleyball rcount = 0.86 > 0.514. Then the relationship between variable (X1) variable (X2) and variable (Y) can be calculated, the truth is tested by F-test and Fcount = 28.8 > 3.81 from the results of these calculations it can be concluded that there is a significant relationship between (X1X2Y) on Volleyball extracurricular activities for female students at SMA Negeri 1 Tembilahan Hulu.
İlköğretim 4. Sınıf Sosyal Bilgiler Dersi Öğretim Programlarına Ait Kazanımların Karşılaştırmalı İncelenmesi
Authors: YALÇIN Ali
Published: September 2023

Bu araştırmanın amacı, 2005, 2018 ve 2023 ilköğretim 4. sınıf sosyal bilgiler dersi öğretim programı, öğrenme alanları kapsamında yer alan kazanımları, nicel ve nitel olarak karşılaştırarak; her üç programda vurgulanan ortak temaları ortaya çıkartmak ve yeni programın bir önceki programa göre değişim ve farklılıklarını ortaya koymaktır. Bu çalışma, nitel araştırma yöntemlerine bağlı kalınarak yürütülmüştür. Araştırmada doküman olarak kullanılan veriler, Milli Eğitim Bakanlığı tarafından hazırlanan 2005, 2018 ve 2023 ilköğretim sosyal bilgiler dersi 4. sınıf öğretim programından oluşmaktadır. Doküman incelemesi yöntemiyle toplanan veriler betimsel analiz yöntemiyle çözümlenmiştir. Araştırmanın inandırıcılığını desteklemek için 2005, 2018 ve 2023 ilköğretim 4. sınıf sosyal bilgiler öğretim programındaki kazanımlar, tablolarda sunulmuştur. Araştırma sonuçlarına göre öğrenme alanlarında belirtilen kazanımların nicel olarak sayısı, 2005 öğretim programında 46 iken 2018 ve 2023 öğretim programında 33’e düştüğü görülmektedir. Nitel olarak 2005 ilköğretim sosyal bilgiler 4 sınıf öğretim programı kazanımında yer alan “Atatürk” isminin, 2018 ve 2023 ilköğretim sosyal bilgiler 4. sınıf öğretim programı kazanımlarında yer verilmediği belirlenmiştir. Ancak genel itibariyle 2005, 2018 ve 2023 sosyal bilgiler öğretim programındaki kazanımların benzer özellikler taşıması dikkat çekicidir. Ayrıca 2018 ve 2023 ilköğretim sosyal bilgiler dersi öğretim programında “etkin vatandaşlık” adlı yeni bir öğrenme alanı oluşturulduğu, bu nedenle bu öğrenme alanındaki kazanımların da “etkin vatandaşlık” kapsamında sunulduğu saptanmıştır. Bu durum, program geliştirme çalışmaları için kazanım ifadelerindeki ayrıntıdan ve benzer açıklamalardan kaçınıldığını göstermektedir. Özellikle teknoloji ve iletişim alanındaki hızlı gelişmeler yeni kazanımların eklenmesini zorunlu kılmıştır. Bu bağlamda, çağımızın siyasi, ekonomik ve toplumsal olayları ışığından hareketle öğrencilerin, bilişsel, duyuşsal ve psikomotor becerilerine uygun kazanımlar eklenebilir veya değiştirilebilir.
Identification and Countermeasures of Network Defamation Crime: Present Situation, Supervision Status, and Criminal Applications
Authors: Qu Renze
Published: September 2023

The network defamation crime presents a serious legal quandary in the digital age. This paper delves into the identification, supervision, criminal applications, and countermeasures of the network defamation crime. First, we clarify the constitutive requirements of the crime and propose a meticulous standard to balance freedom of speech with safeguarding individuals’ rights and interests. Second, we establish an effective onus of proof, thereby alleviating the plaintiff’s load and expediting the judicial process. Simultaneously, we emphasize combating false information to uphold the integrity of cyberspace and further explore the intricate impact of network environments’ anonymity and virtuality on evidence collection, as well as the balance between freedom of speech and individual rights. Finally, this paper puts forward the establishment of transnational cooperation mechanisms and the oversight of social media platforms as a comprehensive strategy to effectively tackle the global challenges in the network defamation crime and contributes valuable insights and suggestions for the wholesome development of cyberspace through detailed discussion.
ESTIMATION OF TREE SPECIES DIVERSITY AND DISTRIBUTION IN THREE COMMUNITIES’ FARMLAND AT DUTSINMA AND SAFANA LOCAL GOVERNMENT AREAS KATSINA STATE.
Authors: Ati Maryam Hassana , Uchechukwu Mary
Published: September 2023

Understanding tree species’ diversity, distribution, and structure is very important in assessing the sustainability of ecosystem conservation and management. This study focused on tree species diversity and distribution in three communities’ farmlands at Dutsin-Ma and Safana local government areas, to assess, identify, enumerate, estimate the richness, and their evenness, and categorise tree species distribution in the study area. A stratified sampling technique was adapted for the study. Two (2) transect lines of 210m length were laid on which sampling plots were established in each of the three study areas. Species richness and diversity were found to be low in all three communities. Azadirachta indica has the highest species richness and diversity in all three communities followed by Adansonia digitata and then Piliostigma thoningii. However, the distribution of trees is not uniform across the study area and varies significantly in their density, diversity, and richness. Tree species at Safana have the highest richness index with a value of 5.383, Turare, with an index value of 5.263 while the least was at Darawa with a value of 3.782. The tree population of the selected study area is presently dominated by the Families of Meliaceae Myrtaceae, Malvaceae, Arecaceae, Moraceae, Pinaceae, Fabaceae, Anacardiaceae, and Combretaceae. The existing flora is dominated by savanna species, particularly those associated with guinea savanna vegetation. Management of forest-savanna should be through fire protection and reforestation programmes and there should be proper awareness of the human activities affecting economic tree species and land management in the study communities.
Inovasi Sosial pada Penanganan Stunting: Penerapan Konsep Bapak Asuh Anak Stunting di Tambak Dahan, Subang, Provinsi Jawa Barat
Authors:   Pusat Riset Kesejahteraan Sosial, Desa dan Konektivitas, Badan Riset dan Inovasi Nasional (BRIN), DKI Jakarta, Indonesia, Wijayanti Febtri , Yudha Raphael , Carolina Carolina , Saparita Rachmini
Published: September 2023

Program Bapak Asuh Anak Stunting (BAAS) merupakan salah satu strategi pemerintah daerah untuk menggugah partisipasi birokrasi khususnya untuk bersama mengupayakan penanganan percepatan penurunan stunting di masyarakat. Karena penanganan stunting membutuhkan kerjasama sinergis berbagai pihak, maka tata kelola kolaboratif menjadi opsi yang layak dipertimbangkan. Tulisan ini membahas tata kelola kolaboratif yang inovatif dengan mengangkat kasus implementasi BAAS melalui dapur sehat (Dashat). Inovasi yang diangkat adalah inovasi sosial, dimana program BAAS melalui Dashat adalah salah satu wujud dari penyelesaian masalah pada masyarakat melalui inovasi sosial. Penelitian menggunakan metode kualitatif, sementara data dan informasi diurai secara deskriptif analitis. Kolaborasi merupakan rekomendasi strategis pada implementasi program BAAS Kabupaten Subang. Kasus di Kecamatan Tambakdahan membuktikan strategi yang tepat untuk mewujudkan tata kelola kolaboratif yang efektif adalah dengan mengakomodasi penerapan inovasi sosial sehingga tujuan publik yang strategis yaitu percepatan penurunan stunting dapat tercapai. Namun, inovasi sosial memerlukan prasyarat yang mendukung antara lain: 1) kepemimpinan, 2) kesamaan pemahaman mengenai urgensi program, 3) komunikasi efektif antar jenjang, 4) kolaborasi yang baik antar pihak, dan 5) modal sosial. Modal sosial sangat penting agar pencegahan dan penangangan stunting mendapatkan perhatian dan bantuan dari masyarakat. Penanganan dan pencegahan stunting memerlukan kerjasama berbagai pihak yang ada di desa, dari pemerintah desa dan terutama masyarakatnya. Tantangan dalam menjalankan inovasi sosial ini bagi pelaku inovasi antara lain: sikap pesimis dari lingkungan sekitar, dukungan dari pemimpin, dan sikap kepemimpinan.
Pekerjaan Sosial Pada Seting Sekolahan: Persepsi Sosial Terhadap Profil Pribadi Kreatif Dalam Perspektif Teori Implisit Kreatifitas
Authors:   Fakultas Ilmu Pendidikan, Universitas Pendidikan Indonesia (UPI), Jawa Barat, Indonesia, Maryani Ineu
Published: September 2023

Pekerja sosial pada setting sekolahan bertanggung jawab memberikan layanan secara menyeluruh disain program untuk pendidikan, karir, pribadi, dan pengembangan sosial untuk seluruh siswa. Penelitian ini bertujuan untuk mendeskripsikan mekanisme teori implisit kreativitas yaitu pengetahuan implisit guru bimbingan dan konseling terhadap profil pribadi kreatif (implisit knowledge of Creative Person) dan persepsi sosial guru bimbingan dan konseling terhadap profil pribadi kreatif (social perception of the creative person). Metode yang digunakan pada penelitian ini adalah kualitatif dengan pendekatan studi kasus. Subject pada penelitian ini terdiri dari tiga orang guru bimbingan dan konseling yang bertugas di Sekolah Menengah Pertama di Kabupaten Bandung Barat - Jawa Barat. Hasil penelitian ini menunjukkan pengetahuan informan terhadap pribadi kreatif dikenal sebagai individu yang penuh semangat dan religius, pantang menyerah, tekun dan memiliki daya imajinasi tinggi. Sedangkan persepsi sosial informan terhadap orang kreatif mengharapkan bahwa keberadaan orang kreatif senantiasa bermanfaat bagi umat, selalu memberikan solusi bagi persoalan di masyarakat dengan karya yang inovatif, serta peduli terhadap kesejahteraan sosial di lingkungan masyarakat . Hasil penelitian ini bermanfaat bagi strategi peningkatan kreativitas melalui persepsi yang positif terhadap orang kreatif sehingga mendorong individu dalam segala bidang untuk meraih pencapaian kreatif dengan melakukan hal-hal baru, belajar hal baru, dan menyelesaikan sesuatu dengan cara dan inovasi baru.
Santa Apolonia de Alejandría. Patrona de los padecimientos dentales. Su martirio e iconografía.
Authors: Ortiz Hidalgo Carlos
Published: September 2023

Resumen: Santa Apolonia de Alejandría fue una mártir cristiana. Sufrió una brutal tortura y amenazada con ser quemada viva si no se retractaba de su cristianismo. Caminó voluntariamente hacia el fuego después de pronunciar una oración, en el 249 d.C. Según la leyenda, Santa Apolonia fue agredida por una turba durante un levantamiento contra los cristianos.   Fue atacada y su tortura incluyó que le destrozaran todos los dientes. Por esta razón, se la considera popularmente como la patrona de la odontología y de quienes padecen dolor de muelas u otros problemas dentales. Muchos pintores medievales pintaron la escena de la tortura de Apolonia en El martirio de Santa Apolonia.
Coaching, Health, and Movement Program (CHAMPS) Taught by Medical Students: A Didactic Curriculum and Program Analysis
Authors: Ronecker, DO Julia C. , Liu, BA, OMSIV Joseph , Newman, MD Ramon E. , VanGarsse, MD Anne M.
Published: September 2023

Purpose: The prevalence of pediatric obesity is increasing in the United States. While physicians are in a unique position to address pediatric obesity, nutrition education and counseling is insufficiently addressed in medical school curriculums. To fill this gap, one Midwest medical school piloted CHAMPS (Coaching, Health, and Movement Program with Students), a program where medical students learn about pediatric obesity and nutrition and coach families toward healthier lifestyle goals.

Method: This study evaluated the effectiveness of a 7-hour didactic curriculum and looked at changes in medical student knowledge, bias, and mentorship skills. The cohort included 35 first-and second-year medical students who completed a pre-test and two post-tests—one post-test after the didactic training and one after the 6-8 week coaching program with a family.

Results: After both the didactic curriculum and coaching sessions, medical students demonstrated statistically significant improvement in knowledge and mentorship skills with regards to pediatric obesity and nutrition. Medical students also reported feeling more confident answering questions and coaching families on healthy lifestyle choices. Medical student bias was unchanged after our intervention.

Conclusion: The CHAMPS program represents a promising experience for medical students and fills a gap in the traditional medical school curriculum.
Injectable nanogel systems for brain drug delivery
Authors: Koyakutty Manzoor , Devassy Greeshma , Das Devika , Nair Shantikumar V
Published: September 2023

The central nervous system (CNS) controls many critical functions, such as intelligence, emotion, sense, and memory, and modulates many other functions of the entire human body. Diseases affecting the CNS are challenging to treat because of the CNS’s sensitive functional and structural features and limited accessibility. The brain is secured from the systemic circulation by a unique biological fence, the blood-brain barrier (BBB), that limits molecular exchange between the peripheral and CNS systems. Most drugs used for treating CNS diseases fail to reach the brain in effective therapeutic concentrations due to the presence of BBB. During the last decade, specifically engineered drug delivery systems (DDS) have offered the opportunity to overcome systemic barriers in brain drug delivery. However, even with the best-engineered nano-carriers, delivering sufficient drug doses into the brain through systemic circulation remains challenging. Here, we review various systems for ‘direct’ drug delivery to the brain using im-plantable or injectable intracranial nano-drug delivery systems (nDDS), which can ensure 100% release of drug to the brain in a sustained or controlled fashion for prolonged periods, bypassing the BBB, thereby radically improving the therapeutic efficacy while minimizing systemic toxicity. Brain injectable nanogels or nanoparticle systems can be considered superior compared to other local drug-delivery systems because they possess better diffusivity of drugs. The nanogels can be injected through minimally invasive procedures, precisely delivering drugs to specific target sites. This review covers a detailed discussion about locally injectable DDS and various nanogel-based drugs, oligonucleotide, and theragnostic delivery systems used for treating brain malignancies, infections, and neurodegenerative diseases.
Corporate Technological Capability as a Driver to Firm Performance: A Study on Firms Listed at the Nairobi Securities Exchange
Authors: Ndungu Samuel Machiri  , Margaret Oloko  , John Karanja Ngugi  , Romanus Odhiambo
Published: September 2023

The aim of this paper was to assess the role played by corporate technological capabilities on firm performance. The ability of a firm to integrate information technology in its operations has been known to be integral in driving organizational success by promoting efficiency and effectiveness. The prevailing underperformance of the listed firms in Kenya raises the question on whether these firms have integrated adequate technology and whether they have what it takes to effectively incorporate technology in their operations, hence the subject of this study. Through a descriptive and exploratory research design, the study surveyed 240 senior management personnel drawn from the 64 listed firms using a structured questionnaire. The data was analysed using SPSS and Amos software for descriptive statistics and structural equation modelling respectively. The findings revealed that technological capabilities had a significant influence on the performance of firms listed at the NSE (R2 = .096; β = 0.150; P=0.0001<0.05). It was concluded that through adequate ICT infrastructure, ICT human skills and the commitment to integrate and accept use of ICT, the listed firms would strengthen their operational efficiency thus record superior performance.
INNOVATIVE APPROACHES TO TEACHING SPEAKING: A CASE STUDY OF SHORT FILM PROJECTS
Authors: Tumanggor Orli Binta
Published: September 2023

This study was conducted as an attempt to find out the effect of applying Transactional Strategies Instruction (TSI) on students' reading comprehension. This study used an experimental design. The population were students from SMA Negeri 1 Onan Ganjang. The sample for this study consisted of sixty first-graders at a senior high school. Two randomly generated groups—one for the experimental group and one for the control group—were used. The control group was taught without applying TSI, while the experimental group was taught with TSI. The instrument for collecting data was an objective multiple-choice test, which consisted of 40 items. The data were analyzed using a t-test. This study shows that teaching reading comprehension by using TSI has a more significant effect than teaching without it.
MINIMIZATION OF RISK AND MAXIMIZATION OF PROFIT ON BEHALF OF BANK BY USING MACHINE LEARNING ALGORITHM
Authors:   Zhejiang University of Science and Technology, Tadiwanashe Wendy Tande
Published: September 2023

The main aim to develop a loan approval prediction model for a bank by utilizing machine learning algorithms. [Objective] The primary objective is to minimize the bank's loss by developing a decision rule for approving or rejecting a loan application based on an applicant's demographic and socio-economic profile. [Method] Three machine learning algorithms, namely Logistic Regression, Random Forest, and Decision Tree, were applied to a German credit dataset to achieve this objective. The data were preprocessed, including converting the target variable to binary, converting character variables to factors, and selecting only numeric variables. The accuracy, sensitivity, and precision of the models were evaluated using crossvalidation, and the results were compared. [Result] The Random Forest model showed the highest accuracy, with an average accuracy of 76.07%, followed by the Decision Tree model with an average accuracy of 71.99%, and Logistic Regression with an average accuracy of 71.62%. The sensitivity evaluation showed that the Decision Tree model had the highest sensitivity, with an average sensitivity of 70.88%, followed by the Logistic Regression model with an average sensitivity of 68.35%, and the Random Forest model with an average sensitivity of 65.86%.[Conclusion] In conclusion, the Random Forest model showed the highest accuracy, while the Decision Tree model had the highest sensitivity. However, all three models showed similar precision scores. Therefore, based on the objective of minimizing the bank's loss, the Decision Tree model may be more suitable as it has higher sensitivity, which means it has a lower chance of approving a loan for a potentially risky applicant. However, further research and testing are necessary before implementing these models in real-world applications.
MONITORING AND REMOVAL OF FAKE PRODUCT REVIEW USING MACHINE LEARNING (ML)
Authors:   Haldia Institute of Technology, Bhattacharya Swarnajit
Published: September 2023

The employment of Natural Language Processing (NLP) as a means for identifying and eliminating counterfeit products from a dataset is a significant endeavor. The current project employs a Machine Learning (ML) Algorithm to discern fraudulent customer reviews within a given dataset. The algorithm leverages predictive modeling techniques to estimate the authenticity of such reviews, and subsequently assess their validity. The prominence of product reviews as a critical determinant of consumer purchasing behavior in the realm of electronic commerce has led to a concerning escalation in the frequency of counterfeit reviews on websites and applications. It is imperative for the prominent Ecommerce firms to confront the issue of counterfeit product reviews, prior to engaging in the procurement of commodities from established entities. The utilization of this particular approach facilitates the rectification process concerning counterfeit product evaluations, thereby eliminating the prevalence of spammers. This proactive measure works to ensure that there is no potential compromise of trust among users of Ecommerce platforms. Through implementation of this initiative, the enterprise's administration can identify spurious evaluations and subsequently implement appropriate measures directed towards their resolution. The present model has been constructed employing the Naïve Bayes Algorithmic approach. By implementing the algorithm, it is possible to discern spam reviews from those that are legitimate, on websites or applications. To tally the individuals who engage in fraudulent online practices, a dataset is necessary. In our study, the "Amazon Academic Dataset" serves as the fitting reference point to prepare the model and can potentially increase the precision and adaptability of the results.
MODELING AND FABRICATION OF 5 – SPEED GEARBOX USING 3D PRINTING WITH OPTIMUM WEIGHT
Authors: Devshette Prof.A.R , Mehta Purvesh , Zambare Saurabh , Patil Ghanshyam , Chaudhari Vinit ,   JSPM’s RSCOE, Pune, Maharashtra, India
Published: September 2023

The main aim of the project is to focus on the modeling and 3D printing of synchromesh gear box and the weight reduction of it using different 3D printing techniques like SSLS, SLA, DLP, FDM. Differential permit each of the driving wheels to rotate at different speeds, while for most vehicles supplying equal torque to each of them. A vehicle's wheels rotate at divergent speeds, mainly when turning corners. The differential is designed to operate a pair of wheels with same torque while permit them to rotate at different speeds. Additive manufacturing education is becoming to widespread adoption. Additive manufacturing is also the manufacturing technology. It is used by multiple industry subsectors, including motor vehicles, aerospace, machinery, electronics, and medical products. It can facilitate the customized production of strong light-weight 3D modeling. This paper describes 3D modeling of five speed transmission is designed and constructed by using AutoCAD software, 3D Mesh software, MakerBot 3D printer and digitizer. This 3D modeling of five speed transmission is good quality through lighter part, can demonstrate easily. The teacher can take 3D modeling of transmission and teach the operations of transmission in the classroom. It can produce the gears, fork, cover and synchronizer sleeves with different color. Many beautiful colors are interested to the students. So, it can use as teaching aids for the engineering students. In this transmission, five forward speed gears are helical type whereas reverse gears are spur type. Design consideration of spur gear and helical gears and shafts are included in this paper. In gear design, the number of teeth, face width, gear tooth features and pitch diameter are calculated. The shafts are designed according to the point of view of the strength.
Effect of right ventricular free wall longitudinal strain on all-cause death in patients with isolated severe tricuspid regurgitation and atrial fibrillation
Authors: Ogawa Mana , Kuwajima Ken , Yamane Takafumi , Hasegawa Hiroko , Yagi Nobuichiro , Shiota Takahiro
Published: September 2023

Background

With the aging population and advanced catheter-based therapy, isolated tricuspid regurgitation (TR) with atrial fibrillation (AF) has gained increased attention; however, data on the prognostic effect of isolated TR with AF are limited because of the small number of patients among those with severe TR. Recently, right ventricular (RV) longitudinal strain by two-dimensional speckle-tracking echocardiography has been reported as an excellent indicator of RV dysfunction in severe TR. However, the prognostic implications of RV longitudinal strain in isolated severe TR associated with AF remain unclear. Therefore, this study aimed to reveal the prognostic value of this index in this population.

Methods

We retrospectively studied patients with severe isolated TR associated with AF in the absence of other etiologies in the Cedars-Sinai Medical Center between April 2015 and March 2018. Baseline clinical and echocardiographic data were studied including RV systolic function evaluated by RV free wall longitudinal strain (FWLS) and conventional parameters. All-cause death was defined as the primary endpoint.

Results

In total, 53 patients (median age, 85 years; female, 60%) with a median follow-up of 433 (60–1567) days were included. Fourteen patients (26%) died, and 66% had right heart failure (RHF) symptoms. By multivariable analysis, reduced RVFWLS was independently associated with all-cause death. Patients with RVFWLS of ≤18% had higher risk of all-cause death adjusted for age (log-rank P = 0.030, adjusted hazard ratio 4.00, 95% confidence interval, 1.11–14.4; P = 0.034). When patients were stratified into four groups by RHF symptoms and RVFWLS, the group with symptomatic and reduced RVFWLS had the worst outcome.

Conclusion

Reduced RVFWLS was independently associated with all-cause death in patients with isolated severe TR and AF. Our subset classification showed the worst outcome from the combination of RHF symptoms and reduced RVFWLS.
The role of autophagy in the treatment of type II diabetes and its complications: a review
Authors: Zhao Xuan , Bie Lu-Yao , Pang Dao-Ran , Li Xiao , Yang Long-Fei , Chen Dan-Dan , Wang Yue-Rui , Gao Yan
Published: September 2023

Type II diabetes mellitus (T2DM) is a chronic metabolic disease characterized by prolonged hyperglycemia and insulin resistance (IR). Its incidence is increasing annually, posing a significant threat to human life and health. Consequently, there is an urgent requirement to discover effective drugs and investigate the pathogenesis of T2DM. Autophagy plays a crucial role in maintaining normal islet structure. However, in a state of high glucose, autophagy is inhibited, resulting in impaired islet function, insulin resistance, and complications. Studies have shown that modulating autophagy through activation or inhibition can have a positive impact on the treatment of T2DM and its complications. However, it is important to note that the specific regulatory mechanisms vary depending on the target organ. This review explores the role of autophagy in the pathogenesis of T2DM, taking into account both genetic and external factors. It also provides a summary of reported chemical drugs and traditional Chinese medicine that target the autophagic pathway for the treatment of T2DM and its complications.
Mechanisms of tertiary lymphoid structure formation: cooperation between inflammation and antigenicity
Authors: Khanal Shrijan , Wieland Andreas , Gunderson Andrew J.
Published: September 2023

To mount an effective anti-tumor immune response capable of controlling or eliminating disease, sufficient numbers of lymphocytes must be recruited to malignant tissue and allowed to sustain their effector functions. Indeed, higher infiltration of T and B cells in tumor tissue, often referred to as “hot tumors”, is prognostic for patient survival and predictive of response to immunotherapy in almost all cancer types. The organization of tertiary lymphoid structures (TLS) in solid tumors is a unique example of a hot tumor whereby T and B lymphocytes aggregate with antigen presenting cells and high endothelial venules reflecting the cellular organization observed in lymphoid tissue. Many groups have reported that the presence of preexisting TLS in tumors is associated with a superior adaptive immune response, response to immunotherapy, and improved survivorship over those without TLS. Accordingly, there is significant interest into understanding the mechanisms of how and why TLS organize so that they can be elicited therapeutically in patients with few or no TLS. Unfortunately, the most commonly used mouse models of cancer do not spontaneously form TLS, thus significantly restricting our understanding of TLS biology. This brief review will summarize our current state of knowledge of TLS neogenesis and address the current gaps in the field.
Elaborating the potential of Artificial Intelligence in automated CAR-T cell manufacturing
Authors: Bäckel Niklas , Hort Simon , Kis Tamás , Nettleton David F. , Egan Joseph R. , Jacobs John J. L. , Grunert Dennis , Schmitt Robert H.
Published: September 2023

This paper discusses the challenges of producing CAR-T cells for cancer treatment and the potential for Artificial Intelligence (AI) for its improvement. CAR-T cell therapy was approved in 2018 as the first Advanced Therapy Medicinal Product (ATMP) for treating acute leukemia and lymphoma. ATMPs are cell- and gene-based therapies that show great promise for treating various cancers and hereditary diseases. While some new ATMPs have been approved, ongoing clinical trials are expected to lead to the approval of many more. However, the production of CAR-T cells presents a significant challenge due to the high costs associated with the manufacturing process, making the therapy very expensive (approx. $400,000). Furthermore, autologous CAR-T therapy is limited to a make-to-order approach, which makes scaling economical production difficult. First attempts are being made to automate this multi-step manufacturing process, which will not only directly reduce the high manufacturing costs but will also enable comprehensive data collection. AI technologies have the ability to analyze this data and convert it into knowledge and insights. In order to exploit these opportunities, this paper analyses the data potential in the automated CAR-T production process and creates a mapping to the capabilities of AI applications. The paper explores the possible use of AI in analyzing the data generated during the automated process and its capabilities to further improve the efficiency and cost-effectiveness of CAR-T cell production.
Does rDLPFC activity alter trust? Evidence from a tDCS study
Authors: Sun Letian , Lu Xinbo , Zheng Haoli , Zeng Lulu , Zheng Wanjun , Wang Jinjin
Published: September 2023

Trust plays an important role in the human economy and people’s social lives. Trust is affected by various factors and is related to many brain regions, such as the dorsolateral prefrontal cortex (DLPFC). However, few studies have focused on the impact of the DLPFC on trust through transcranial direct current stimulation (tDCS), although abundant psychology and neuroscience studies have theoretically discussed the possible link between DLPFC activity and trust. In the present study, we aimed to provide evidence of a causal relationship between the rDLPFC and trust behavior by conducting multiple rounds of the classical trust game and applying tDCS over the rDLPFC. We found that overall, anodal stimulation increased trust compared with cathodal stimulation and sham stimulation, while the results in different stages were not completely the same. Our work indicates a causal relationship between rDLPFC excitability and trust behavior and provides a new direction for future research.
Characterizing nutrient patterns of food items in adolescent diet using data from a novel citizen science project and the US National Health and Nutrition Examination Survey (NHANES)
Authors: Treitler Jonah T. , Tekle Senait , Ushe Jennifer , Zanin Linda , Capshaw Teri , Tardieu Gregory , Libin Alexander , Zeng Qing
Published: September 2023

Introduction

A healthy diet is essential for promoting good health during adolescence and mitigating disease risks in adulthood. This underscores the need for improved nutrition education and increased access to healthier food choices. However, the accuracy of dietary data poses a significant challenge in nutritional research.

Methods

We utilized and analyzed a novel dietary record dataset collected through a high school citizen science project to address this issue. We focused on nutrients rather than food groups to characterize adolescent dietary patterns. The same analyses were performed on the 2019–2021 National Health and Nutrition Examination Survey data for comparison.

Results

Based on the U.S. Food and Drug Administration’s recommended daily value (DV) for nutrients, the majority of food items in our citizen science dataset are low (i.e., <5% DV) in lipids, fiber, potassium, calcium, iron, sugar, and cholesterol. Only a minority of items are high (i.e., >20% DV) in macro and micronutrients. The clustering analysis identified nine food clusters with distinct nutrient profiles that vary significantly in size. The analyses on the NHANES data yielded similar findings, but with higher proportions of foods high in energy, lipids, carbohydrates, sugar, iron, and sodium compared with those of the citizen science dataset.

Discussion

This study demonstrates the potential of citizen science projects in gathering valuable dietary data and understanding adolescent nutrient intake. Identifying critical nutrient gaps can guide targeted nutrition education and the provision of accessible healthier food options, leading to positive health outcomes during adolescence and beyond.
Estimate of the incidence of PANDAS and PANS in 3 primary care populations
Authors: Wald Ellen R. , Eickhoff Jens , Flood Grace E. , Heinz Michael V. , Liu Daniel , Agrawal Alisha , Morse Richard P. , Raney Veronica M. , Veerapandiyan Aravindhan , Madan Juliette C.
Published: September 2023

Objective

Pediatric Autoimmune Neuropsychiatric Disorder Associated with Streptococcal infection (PANDAS) and Pediatric Acute-Onset Neuropsychiatric syndrome (PANS) are presumed autoimmune complications of infection or other instigating events. To determine the incidence of these disorders, we performed a retrospective review for the years 2017–2019 at three academic medical centers.

Methods

We identified the population of children receiving well-child care at each institution. Potential cases of PANS and PANDAS were identified by including children age 3–12 years at the time they received one of five new diagnoses: avoidant/restrictive food intake disorder, other specified eating disorder, separation anxiety disorder of childhood, obsessive-compulsive disorder, or other specified disorders involving an immune mechanism, not elsewhere classified. Tic disorders was not used as a diagnostic code to identify cases. Data were abstracted; cases were classified as PANDAS or PANS if standard definitions were met.

Results

The combined study population consisted of 95,498 individuals. The majority were non-Hispanic Caucasian (85%), 48% were female and the mean age was 7.1 (SD 3.1) years. Of 357 potential cases, there were 13 actual cases [mean age was 6.0 (SD 1.8) years, 46% female and 100% non-Hispanic Caucasian]. The estimated annual incidence of PANDAS/PANS was 1/11,765 for children between 3 and 12 years with some variation between different geographic areas.

Conclusion

Our results indicate that PANDAS/PANS is a rare disorder with substantial heterogeneity across geography and time. A prospective investigation of the same question is warranted.
Effects of measurement methods and growing conditions on phenotypic expression of photosynthesis in seven diverse rice genotypes
Authors: Reavis Megan , Purcell Larry C. , Pereira Andy , Naithani Kusum
Published: September 2023

Introduction

Light response curves are widely used to quantify phenotypic expression of photosynthesis by measuring a single sample and sequentially altering light intensity within a chamber (sequential method) or by measuring different samples that are each acclimated to a different light level (non-sequential method). Both methods are often conducted in controlled environments to achieve steady-state results, and neither method involves equilibrating the entire plant to the specific light level.

Methods

Here, we compare sequential and non-sequential methods in controlled (greenhouse), semi-controlled (plant grown in growth chamber and acclimated to field conditions 2-3 days before measurements), and field environments. We selected seven diverse rice genotypes (five genotypes from the USDA rice minicore collection: 310588, 310723, 311644, 311677, 311795; and 2 additional genotypes: Nagina 22 and Zhe 733) to understand (1) the limitations of different methods, and (2) phenotypic plasticity of photosynthesis in rice grown under different environments.

Results

Our results show that the non-sequential method was time-efficient and captured more variability of field conditions than the sequential method, but the model parameters were generally similar between two methods except the maximum photosynthesis rate (Amax).Amaxwas significantly lower across all genotypes under greenhouse conditions compared to the growth chamber and field conditions consistent with prior work, but surprisingly the apparent quantum yield (α) and the mitochondrial respiration (Rd) were generally not different among growing environments or measurement methods.

Discussion

Our results suggest that field conditions are best suited to quantify phenotypic differences across different genotypes and nonsequential method was better at capturing the variability in photosynthesis.
Genome-wide analysis of the GRAS gene family in Liriodendron chinense reveals the putative function in abiotic stress and plant development
Authors: Weng Yuhao , Chen Xinying , Hao Zhaodong , Lu Lu , Wu Xinru , Zhang Jiaji , Wu Jingxiang , Shi Jisen , Chen Jinhui
Published: September 2023

Introduction

GRAS genes encode plant-specific transcription factors that play essential roles in plant growth and development. However, the members and the function of the GRAS gene family have not been reported in Liriodendron chinense. L. chinense, a tree species in the Magnolia family that produces excellent timber for daily life and industry. In addition, it is a good relict species for plant evolution research.

Methods

Therefore, we conducted a genome-wide study of the LcGRAS gene family and identified 49 LcGRAS genes in L. chinense.

Results

We found that LcGRAS could be divided into 13 sub-groups, among which there is a unique branch named HAM-t. We carried out RNA sequencing analysis of the somatic embryos from L. chinense and found that LcGRAS genes are mainly expressed after heart-stage embryo development, suggesting that LcGRAS may have a function during somatic embryogenesis. We also investigated whether GRAS genes are responsive to stress by carrying out RNA sequencing (RNA-seq) analysis, and we found that the genes in the PAT subfamily were activated upon stress treatment, suggesting that these genes may help plants survive stressful environments. We found that PIF was downregulated and COR was upregulated after the transient overexpression of PATs, suggesting that PAT may be upstream regulators of cold stress.

Discussion

Collectively, LcGRAS genes are conserved and play essential roles in plant development and adaptation to abiotic stress.
In models we trust: preregistration, large samples, and replication may not suffice
Authors: Spiess Martin , Jordan Pascal
Published: September 2023

Despite discussions about the replicability of findings in psychological research, two issues have been largely ignored: selection mechanisms and model assumptions. Both topics address the same fundamental question: Does the chosen statistical analysis tool adequately model the data generation process? In this article, we address both issues and show, in a first step, that in the face of selective samples and contrary to common practice, the validity of inferences, even when based on experimental designs, can be claimed without further justification and adaptation of standard methods only in very specific situations. We then broaden our perspective to discuss consequences of violated assumptions in linear models in the context of psychological research in general and in generalized linear mixed models as used in item response theory. These types of misspecification are oftentimes ignored in the psychological research literature. It is emphasized that the above problems cannot be overcome by strategies such as preregistration, large samples, replications, or a ban on testing null hypotheses. To avoid biased conclusions, we briefly discuss tools such as model diagnostics, statistical methods to compensate for selectivity and semi- or non-parametric estimation. At a more fundamental level, however, a twofold strategy seems indispensable: (1) iterative, cumulative theory development based on statistical methods with theoretically justified assumptions, and (2) empirical research on variables that affect (self-) selection into the observed part of the sample and the use of this information to compensate for selectivity.
Selecting the best optimizers for deep learning–based medical image segmentation
Authors: Mortazi Aliasghar , Cicek Vedat , Keles Elif , Bagci Ulas
Published: September 2023

Purpose

The goal of this work is to explore the best optimizers for deep learning in the context of medical image segmentation and to provide guidance on how to design segmentation networks with effective optimization strategies.

Approach

Most successful deep learning networks are trained using two types of stochastic gradient descent (SGD) algorithms: adaptive learning and accelerated schemes. Adaptive learning helps with fast convergence by starting with a larger learning rate (LR) and gradually decreasing it. Momentum optimizers are particularly effective at quickly optimizing neural networks within the accelerated schemes category. By revealing the potential interplay between these two types of algorithms [LR and momentum optimizers or momentum rate (MR) in short], in this article, we explore the two variants of SGD algorithms in a single setting. We suggest using cyclic learning as the base optimizer and integrating optimal values of learning rate and momentum rate. The new optimization function proposed in this work is based on the Nesterov accelerated gradient optimizer, which is more efficient computationally and has better generalization capabilities compared to other adaptive optimizers.

Results

We investigated the relationship of LR and MR under an important problem of medical image segmentation of cardiac structures from MRI and CT scans. We conducted experiments using the cardiac imaging dataset from the ACDC challenge of MICCAI 2017, and four different architectures were shown to be successful for cardiac image segmentation problems. Our comprehensive evaluations demonstrated that the proposed optimizer achieved better results (over a 2% improvement in the dice metric) than other optimizers in the deep learning literature with similar or lower computational cost in both single and multi-object segmentation settings.

Conclusions

We hypothesized that the combination of accelerated and adaptive optimization methods can have a drastic effect in medical image segmentation performances. To this end, we proposed a new cyclic optimization method (Cyclic Learning/Momentum Rate) to address the efficiency and accuracy problems in deep learning–based medical image segmentation. The proposed strategy yielded better generalization in comparison to adaptive optimizers.
From egg to slaughter: monitoring the welfare of Nile tilapia, Oreochromis niloticus, throughout their entire life cycle in aquaculture
Authors: Pedrazzani Ana Silvia , Cozer Nathieli , Quintiliano Murilo Henrique , Tavares Camila Prestes dos Santos , Biernaski Vilmar , Ostrensky Antonio
Published: September 2023

The primary aim of this study was to comprehensively evaluate the welfare of Nile tilapia(Oreochromis niloticus)throughout their entire life cycle within aquaculture, spanning from reproduction to slaughter. The methodology was structured to identify welfare indicators closely aligned with the principles of animal freedoms defined by the Farm Animal Council, encompassing environmental, health, nutritional, behavioral, and psychological freedom. Notably, psychological freedom was inherently considered within the behavioral and physical analyses of the animals. To accomplish this, an integrative systematic literature review was conducted to define precise indicators and their corresponding reference values for each stage of tilapia cultivation. These reference values were subsequently categorized using a scoring system that assessed the deviation of each indicator from established ideal (score 1), tolerable (score 2), and critical (score 3) ranges for the welfare of the target species. Subsequently, a laboratory experiment was executed to validate the pre-selected health indicators, specifically tailored for the early life stages of tilapia. This test facilitated an assessment of the applicability of these indicators under operational conditions. Building on the insights gained from this experimentation, partial welfare indices (PWIs) were computed for each assessed freedom, culminating in the derivation of a general welfare index (GWI). Mathematical equations were employed to calculate these indices, offering a quantitative and standardized measure of welfare. This approach equips tilapia farmers and processors with the tools necessary for the continuous monitoring and enhancement of their production systems and stimulate the adoption of more sustainable and ethical practices within the tilapia farming.
Continuous professional development — innovative training methods of average health workers
Authors:   SBHI SR Volga Central District Hospital, Volzhsky District, Samara Region, Russia, Inozemtseva S. V.
Published: September 2023

The article presents the experience of optimizing the work of an educational and methodological office in a medical organization. A study to determine the level of nursing staff satisfaction with the learning process was conducted. Aim. Improving (optimizing) the activities of the educational and methodological office and enhancing the qualit y of work of medical personnel. Results. Obtaining high quality indicators in the work of the nursing staff of a medical organization is directly related to the optimization of the work of the educational and methodological office. Conducting additional theoretical and practical classes on identified violations, credits and testing of nursing staff, regular training of junior and middle medical personnel on nosocomial infection, as well as targeted internal audits aim nurses at a more serious and competent attitude to the prevention of nosocomial infection and occupational infections. Conclusion. The strategy for the development of continuous education in the workplace is one of the most successful tools to meet the challenges of compliance of the capabilities of nursing staff with the high demands of modern healthcare.