bluuebunny/crossref_metadata_2025 huggingface dataset:
What Were the Most Populartafsīrs in Islamic History? Part 1: An Assessment of the Manuscript Record and the State oftafsīrStudies
Authors: Ross Samuel J.
Published: March 2024

Hitherto, the field of tafsīr studies has been beset by several challenges that have hindered its ability to produce a reliable historical outline of the genre. These challenges include: (1) the voluminous nature of our sources, both in terms of the sheer number of works and their individual length; (2) the fact that the overwhelming majority of works continue to be available only in manuscript form; (3) the tendency of previous scholarship to focus on the ‘classical’ period, leaving the post-classical tafsīr tradition largely unexplored, especially the ḥawāshī; and (4) our limited knowledge about which works were historically popular, when, where, and for whom.

This article shares the findings of a multi-year project to convert the most important union catalogue of Arabic tafsīr manuscripts, al-Fihris al-shāmil, into a searchable database and to use this database to pose and answer questions that were hitherto difficult to explore. These questions include: (1) What were the most longitudinally popular commentaries on the Qur’an as suggested by counts of extant manuscripts and their geographic distribution today? (2) To what extent have academic scholars studied these works? It is hoped that these findings will assist the field in planning future scholarly projects and in ultimately developing a more reliable outline of the tafsīr tradition.
Analisis Kinerja Sistem Pakar Diagnosis Coronavirus Disease Menggunakan Metode Certainty Factor
Authors: Pratama Moch Deny , Affandi Luqman , Satya Dian Nugraha Bagas
Published: March 2024

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), atau Covid-19, merupakan penyakit virus yang sangat menular melalui kontak fisik atau sentuhan dengan benda yang telah tersentuh oleh individu terjangkit. Pandemi ini memberikan dampak besar, termasuk perubahan signifikan dalam gaya hidup sehari-hari dan pembatasan kontak sosial dengan banyak orang. Kesulitan dalam mendeteksi keberadaan penyakit ini disebabkan oleh kurangnya pemahaman masyarakat, memungkinkan penyebarannya menjadi sangat cepat. Terdapat kendala dengan adanya keterbatasan konsultasi dan fasilitas Rapid Test dan Swab Test yang belum merata dan harganya relatif mahal sehingga tidak semua orang mau melakukan pemeriksaan. Tujuan penelitian ini adalah membangun Sistem Pakar untuk melakukan diagnosis awal terhadap penyakit virus corona menggunakan Metode Certainty Factor yang mempermudah dalam memberikan hasil diagnosis, pengetahuan, serta solusi. Certainty Factor dapat bekerja dengan ketidakpastian melalui pemrosesan data untuk mengambil kesimpulan hasil diagnosis penyakit dengan persentase perhitungan nilai kepastian. Penelitian ini berfokus pada gejala klinis Covid-19, sistem ini diharapkan dapat membantu dalam mengantisipasi penyebaran virus dengan memberikan solusi yang tepat waktu. Metode Certainty Factor dipilih karena kemampuannya mengolah data yang memiliki ketidakpastian, menjaga keakuratan hasil, dan dianggap cocok untuk implementasi sistem pakar dengan input data yang tidak pasti. Penelitian ini mengusulkan solusi yang relevan dengan data kondisi beberapa gejala komorbid, agnosmia, dan ageusia untuk melakukan identifikasi penyakit menjadi dua rule kelas yaitu Suspect dan Probable Covid-19. Berdasarkan pengujian fungsionalitas secara black box, didapatkan tingkat akurasi sebesar 100%, sementara berdasarkan pengujian validitas pakar, tingkat akurasi sebesar 100%, dan pengujian validitas perhitungan memiliki tingkat akurasi uji validitas sebesar 87.5%.
Rancang Bangun Sistem Informasi Berbasis Website untuk Monitoring RAB di Unit Pelaksana Transmisi PT. PLN Salatiga dengan Blackbox Testing
Authors: Dewi Purnamasari  , Siti Umi Damayanti  , Jumrianto  , Nisrina Qurratu Aini
Published: March 2024

Pengelolaan Rencana Anggaran Biaya (RAB) di suatu perusahaan sangat perlu dilakukan agar perusahaan dapat memberikan dampak efisien dalam serapan anggaran dan pelaksanaan program berjalan sesuai dengan yang direncanakan, selain itu juga digunakan untuk memperkirakan biaya komponen-komponen dengan mempertimbangkan waktu pekerjaan dilaksanakan. Rencana Anggaran Biaya sebagai perancangan yang digunakan untuk memperkirakan biaya dan waktu yang dibutuhkan untuk melaksanakan suatu kegiatan. Permasalahan utama pada PT. PLN Unit Pelaksana Transmisi (UPT) Salatiga memiliki bidang kerja pembuatan RAB. Pada proses pembuatan sampai pekerjaan dalam RAB selesai masih dilakukan secara manual dengan menggunakan Google SpreadSheet. Sistem informasi monitoring Rencana Anggaran Biaya berbasis website dirancang untuk membantu PT. PLN UPT Salatiga. Sistem ini bertujuan untuk memonitoring berkas RAB karena sering terjadinya berkas RAB yang terhenti, tidak ditindaklanjuti, proses yang lama, serta berkas yang hilang atau tidak ditemukan. Karena permasalahan tersebut sering dirasakan PT. PLN UPT Salatiga yang menghambat pekerjaan di berbagai bidang yang ada di perusahaan tersebut, dibutuhkan sistem informasi berbasis website untuk monitoring RAB. Penelitian ini berhasil membangun dan mengembangkan sistem informasi berbasis website untuk monitoring RAB dengan menggunakan metode waterfall dan menggunakan pengujian black box testing. Pengujian menunjukkan masing-masing tombol di sistem RAB berjalan tanpa error dengan pengujian masing masing form dilakukan sebanyak lima iterasi. Sistem ini diharapkan dapat menyelesaikan permasalahan yang ada di perusahaan PT. PLN UPT Salatiga terutama dalam monitoring RAB sehingga mempercepat dalam hal komputasi dan hasil penelitian ini menggunakan lima pengujian dengan black box testing yang terdiri dari pengujian form login, form dashboard, form data users, form monitoring RAB, form laporan monitoring RAB yang menunjukkan keberhasilan pengujian aplikasi website RAB sesuai yang diharapkan
Klasifikasi Citra Candi Berdasarkan Tekstur Bentuk Menggunakan Convolutional Neural Network
Authors: Devi Oktaviani  , Muhammad Resa Arif Yudianto  , Maimunah  , Pristi Sukmasetya  , Rofi Abul Hasani
Published: March 2024

Candi merupakan bangunan kuno peninggalan Hindu-Buddha yang terbuat dari batu yang digunakan sebagai tempat ibadah. Beberapa candi memiliki persamaan yang signifikan khususnya dari segi struktur bangunan pada candi tersebut. Penelitian ini mengeksplorasi penggunaan Convolutional Neural Network (CNN) dengan arsitektur ResNet-50 untuk mengklasifikasikan citra candi di Jawa Tengah, Indonesia. Pariwisata di provinsi ini memiliki nilai ekonomi dan kultural yang tinggi, terutama dengan warisan sejarah seperti Candi Borobudur dan Candi Mendut. Dengan banyaknya candi yang memiliki struktur serupa, penelitian ini memanfaatkan teknologi deep learning, khususnya CNN, untuk mengklasifikasikan citra berdasarkan tekstur bentuk. Dengan pengumpulan data menggunakan teknik scrapping, diperoleh 400 dataset citra dari kedua candi tersebut. Proses Image pre-processing melibatkan resizing, grayscaling. Pada penelitian ini dilakukan 2 jenis skenario pengolahan citra sebelum diproses dengan CNN yaitu menggunakan CLAHE dan deteksi tepi dengan metode Canny. Dua skenario tersebut dievaluasi, dan memperoleh akurasi tertinggi sebesar 95% untuk penggunaan CLAHE sedangkan saat menggunakan deteksi tepi Canny didapatkan akurasi sebesar 91,25%. Proses klasifikasi menggunakan arsitektur ResNet-50, dan hasilnya menunjukkan keunggulan penggunaan CLAHE dengan selisih akurasi 3,75% dibandingkan dengan deteksi tepi Canny. Penerapan model mencakup desain Graphical User Interface (GUI) untuk memudahkan pengguna dalam mengklasifikasikan citra candi. Hasil akhir menunjukkan bahwa CLAHE merupakan metode image pre-processing paling efektif untuk meningkatkan akurasi klasifikasi citra candi. Temuan ini memberikan kontribusi pada pemahaman tentang penerapan teknologi deep learning dalam mendukung identifikasi dan promosi warisan budaya, terutama di sektor pariwisata
Rancang Bangun Sistem Informasi Perpustakaan Berbasis Website di SMAN Ploso Menggunakan Algoritma Apriori
Authors: Vista Candra Bella , Nugraha Girindra Fajar , Cinderatama Toga Aldila
Published: March 2024

Proses manajemen seperti pencatatan peminjaman, pengembalian, dan inventaris buku yang ada di Perpustakaan SMAN Ploso masih menggunakan proses pencatatan pada buku. Selain itu, proses pengembalian buku belum terorganisir dengan baik, karena masih terdapat anggota perpustakaan yang mengembalikan buku pada rak yang tidak semestinya. Maka dari itu, sistem ini dibuat bertujuan untuk memberikan kemudahan dalam proses pengelolaan data perpustakaan dan memberikan rekomendasi penempatan buku dan pengadaan buku berdasarkan pola peminjaman.

Sistem ini memiliki fitur pengelolaan data perpustakaan seperti data buku, anggota, peminjaman, pengembalian, rekomendasi penempatan buku berdasarkan kategori pada data transaksi, rekomendasi pengadaan buku berdasarkan data transaksi, laporan, dan denda. Pada sistem ini admin dapat melakukan perhitungan Algoritma Apriori pada menu penempatan buku dengan memasukkan rentan waktu data peminjaman, nilai minimum support, dan nilai minimum confidence. Berdasarkan pengujian yang dilakukan, admin memasukkan rentan waktu bulan Januari – Februari. Kemudian untuk nilai minimum support sebesar 10% dan nilai minimum confidence sebesar 60%. Berdasarkan analisis yang telah dilakukan, pemilihan nilai minimum support 10% dan nilai minimum confidence 60% memperoleh hasil yang ideal, karena itemset dan aturan asosiasi yang muncul memiliki keterkaitan yang signifikan. Dari nilai-nilai tersebut kemudian diproses oleh sistem dan menghasilkan nilai confidence 4 itemset, di mana masing-masing itemset tersebut memiliki nilai persentase confidence yang telah memenuhi nilai minimum confidence. Dari hasil yang diperoleh kategori kimia dan matematika sebesar 100%, kategori ekonomi dan geografi sebesar 62,5%, kategori geografi dan ekonomi sebesar 83,3%, kategori fisika dan matematika sebesar 80%. Dari hasil nilai confidence tersebut dapat digunakan sebagai rekomendasi penempatan buku maupun pengadaan buku.
Research advances of polycomb group proteins in regulating mammalian development
Authors: Li Yan , Mo Yanxiang , Chen Chen , He Jin , Guo Zhiheng
Published: March 2024

Polycomb group (PcG) proteins are a subset of epigenetic factors that are highly conserved throughout evolution. In mammals, PcG proteins can be classified into two muti-proteins complexes: Polycomb repressive complex 1 (PRC1) and PRC2. Increasing evidence has demonstrated that PcG complexes play critical roles in the regulation of gene expression, genomic imprinting, chromosome X-inactivation, and chromatin structure. Accordingly, the dysfunction of PcG proteins is tightly orchestrated with abnormal developmental processes. Here, we summarized and discussed the current knowledge of the biochemical and molecular functions of PcG complexes, especially the PRC1 and PRC2 in mammalian development including embryonic development and tissue development, which will shed further light on the deep understanding of the basic knowledge of PcGs and their functions for reproductive health and developmental disorders.
Urban delineation through a prism of intraday commute patterns
Authors: Bogomolov Yuri , Belyi Alexander , Sobolevsky Stanislav
Published: March 2024

Introduction

Urban mobility patterns are crucial for effective urban and transportation planning. This study investigates the dynamics of urban mobility in Brno, Czech Republic, utilizing the rich dataset provided by passive mobile phone data. Understanding these patterns is essential for optimizing infrastructure and planning strategies.

Methods

We developed a methodological framework that incorporates bidirectional commute flows and integrates both urban and suburban commute networks. This comprehensive approach allows for a detailed representation of Brno's mobility landscape. By employing clustering techniques, we aimed to identify distinct mobility patterns within the city.

Results

Our analysis revealed consistent structural features within Brno's mobility patterns. We identified three distinct clusters: a central business district, residential communities, and an intermediate hybrid cluster. These clusters highlight the diversity of mobility demands across different parts of the city.

Discussion

The study demonstrates the significant potential of passive mobile phone data in enhancing our understanding of urban mobility patterns. The insights gained from intraday mobility data are invaluable for transportation planning decisions, allowing for the optimization of infrastructure utilization. The identification of distinct mobility patterns underscores the practical utility of our methodological advancements in informing more effective and efficient transportation planning strategies.
Double somatic mutations in CTNNB1 and GNA11 in an aldosterone-producing adenoma
Authors: Nanba Kazutaka , Blinder Amy R. , Udager Aaron M. , Hirokawa Yuusuke , Miura Takayoshi , Okuno Hiroshi , Moriyoshi Koki , Yamazaki Yuto , Sasano Hironobu , Yasoda Akihiro , Satoh-Asahara Noriko , Rainey William E. , Tagami Tetsuya
Published: March 2024

Double somatic mutations in CTNNB1 and GNA11/Q have recently been identified in a small subset of aldosterone-producing adenomas (APAs). As a possible pathogenesis of APA due to these mutations, an association with pregnancy, menopause, or puberty has been proposed. However, because of its rarity, characteristics of APA with these mutations have not been well characterized. A 46-year-old Japanese woman presented with hypertension and hypokalemia. She had two pregnancies in the past but had no history of pregnancy-induced hypertension. She had regular menstrual cycle at presentation and was diagnosed as having primary aldosteronism after endocrinologic examinations. Computed tomography revealed a 2 cm right adrenal mass. Adrenal venous sampling demonstrated excess aldosterone production from the right adrenal gland. She underwent right laparoscopic adrenalectomy. The resected right adrenal tumor was histologically diagnosed as adrenocortical adenoma and subsequent immunohistochemistry (IHC) revealed diffuse immunoreactivity of aldosterone synthase (CYP11B2) and visinin like 1, a marker of the zona glomerulosa (ZG), whereas 11β-hydroxylase, a steroidogenic enzyme for cortisol biosynthesis, was mostly negative. CYP11B2 IHC-guided targeted next-generation sequencing identified somatic CTNNB1 (p.D32Y) and GNA11 (p.Q209H) mutations. Immunofluorescence staining of the tumor also revealed the presence of activated β-catenin, consistent with features of the normal ZG. The expression patterns of steroidogenic enzymes and related proteins indicated ZG features of the tumor cells. PA was clinically and biochemically cured after surgery. In conclusion, our study indicated that CTNNB1 and GNA11-mutated APA has characteristics of the ZG. The disease could occur in adults with no clear association with pregnancy or menopause.
Establishment and validation of a nomogram for subsequent first-cycle live births in patients diagnosed with recurrent implantation failure: a population-based analysis
Authors: Zhang Yunian , Gong Xiaoyun , Zhang Manli , Zhu Yuejie , Wang Peng , Wang Zhihui , Liu Chen , La Xiaolin , Ding Jianbing
Published: March 2024

Background

The inability of patients with recurrent implantation failure (RIF) to achieve pregnancy and a live birth after multiple high-quality embryo transfer treatments has been recognized as a major obstacle to successful application of artificial reproductive technologies. The objective of this study was to establish and validate a nomogram for prediction of subsequent first-cycle live births to guide clinical practice in patients diagnosed with RIF.

Methods

A total of 538 patients who underwent in vitro fertilization/intracytoplasmic sperm injection treatment and were first diagnosed with RIF at the Reproductive Center of the First Affiliated Hospital of Xinjiang Medical University between January 2017 and December 2020 were enrolled. The patients were randomly divided into a training cohort (n=408) and a validation set (n=175) in a ratio of 7:3. A nomogram model was constructed using the training set based on the results of univariate and multivariate logistic regression analyses and validated in the validation set.

Results

Age, body mass index, duration of RIF, endometrial thickness, type of embryo transferred, and number of previous biochemical pregnancies were included in the nomogram for prediction of subsequent first-cycle live births in patients diagnosed with RIF. Analysis of the area under the receiver-operating characteristic curve, calibration plots, and decision curve analysis showed that our predictive model for live births had excellent performance.

Conclusion

We have developed and validated a novel predictive model that estimates a woman’s chances of having a live birth after a diagnosis of RIF and provides clinicians with a personalized clinical decision-making tool.
Frequency emergency control strategy in power systems considering the participation of energy storage clusters
Authors: Liu Yang , Xie Pingping , Wu Guobing , Chen Yue , Lin Xu , Lu Qiuyu
Published: March 2024

Recently, the power systems with a high penetration of renewables and power electronics have come into being. In these power systems, complex system dynamics, emergency faults, and insufficient frequency regulation reserve pose threats to system frequency stability. Based on the clustering development of energy storage, to ensure the system frequency stability when emergency faults occur, this paper proposes a decentralized frequency emergency control (FEC) strategy considering the participation of energy storage clusters (ESCs). First, the overall framework of the optimal-droop-based FEC strategy is introduced, which achieves the coordination between FEC and conventional frequency regulation strategies. Second, to appropriately allocate the unbalanced power among the generators and ESCs, a general design method for optimal droop coefficients is proposed, which is applicable to various control objectives. The optimality of the droop coefficients is rigorously proven. This case study is carried out on an electromagnetic transient simulation platform, and the simulation results verify the effectiveness and optimality of the proposed FEC strategy.
Enhanced defluoridation by nano-crystalline alum-doped hydroxyapatite and artificial intelligence (AI) modeling approach
Authors: Varma Nitin Pratap , Sinha Alok , Gupta Sunil Kumar , Mahato Jaydev Kumar , Chand Priyankar
Published: March 2024

The study aimed to investigate the defluoridation capacity of nano-hydroxyapatite (HAP) [Ca10(PO4)6(OH)2] and alum-doped hydroxyapatite (AHAP) [Ca8Al(PO4)6.(OH)2] as an environmental friendly adsorbent. The physicochemical characteristics of both the material (HAP and AHAP) were examined using XRD, FE-SEM-EDS, and BET techniques. The batch adsorption study revealed a fluoride removal efficiency of up to 83% (AHAP) and 74% (HAP) under acidic conditions (pH-2). The doping of alum alters the surface chemistry and enhances the affinity of AHAP for fluoride adsorption. The pseudo-second-order kinetic (R2–0.9941) and Langmuir isotherm (R2–0.9425) models best describe the adsorption mechanism and behavior. The thermodynamic analysis indicated the spontaneous and endothermic nature of the adsorption process. The study also tested the applicability of the artificial neural network (ANN) modeling approach using MATLAB R2013a to simulate the simulated absorptive efficiency of AHAP. This study suggests that AHAP proved an effective adsorbent for defluoridation.
Linear epitopes of bony fish β-parvalbumins
Authors: Franciskovic Eric , Thörnqvist Linnea , Greiff Lennart , Gasset Maria , Ohlin Mats
Published: March 2024

Introduction

Fish β-parvalbumins are common targets of allergy-causing immunity. The nature of antibody responses to such allergens determines the biological outcome following exposure to fish. Specific epitopes on these allergens recognised by antibodies are incompletely characterised.

Methods

High-content peptide microarrays offer a solution to the identification of linear epitopes recognised by antibodies. We characterized IgG and IgG4 recognition of linear epitopes of fish β-parvalbumins defined in the WHO/IUIS allergen database as such responses hold the potential to counter an allergic reaction to these allergens. Peripheral blood samples, collected over three years, of 15 atopic but not fish-allergic subjects were investigated using a microarray platform that carried every possible 16-mer peptide of known isoforms and isoallergens of these and other allergens.

Results

Interindividual differences in epitope recognition patterns were observed. In contrast, reactivity patterns in a given individual were by comparison more stable during the 3 years-course of the study. Nevertheless, evidence of the induction of novel specificities over time was identified across multiple regions of the allergens. Particularly reactive epitopes were identified in the D helix of Cyp c 1 and in the C-terminus of Gad c 1 and Gad m 1.02. Residues important for the recognition of certain linear epitopes were identified. Patterns of differential recognition of isoallergens were observed in some subjects.

Conclusions

Altogether, comprehensive analysis of antibody recognition of linear epitopes of multiple allergens enables characterisation of the nature of the antibody responses targeting this important set of food allergens.
Causal associations between circulating cytokines and risk of sepsis and related outcomes: a two-sample Mendelian randomization study
Authors: Zhi Feng , Ma Jia-wei , Ji Dan-dan , Bao Jie , Li Qian-qian
Published: March 2024

Introduction

Sepsis represents a critical medical condition that arises due to an imbalanced host reaction to infection. Central to its pathophysiology are cytokines. However, observational investigations that explore the interrelationships between circulating cytokines and susceptibility to sepsis frequently encounter challenges pertaining to confounding variables and reverse causality.

Methods

To elucidate the potential causal impact of cytokines on the risk of sepsis, we conducted two-sample Mendelian randomization (MR) analyses. Genetic instruments tied to circulating cytokine concentrations were sourced from genome-wide association studies encompassing 8,293 Finnish participants. We then evaluated their links with sepsis and related outcomes using summary-level data acquired from the UK Biobank, a vast multicenter cohort study involving over 500,000 European participants. Specifically, our data spanned 11,643 sepsis cases and 474,841 controls, with subsets including specific age groups, 28-day mortality, and ICU-related outcomes.

Results and Discussion

MR insights intimated that reduced genetically-predicted interleukin-10 (IL-10) levels causally correlated with a heightened sepsis risk (odds ratio [OR] 0.68, 95% confidence interval [CI] 0.52-0.90, P=0.006). An inverse relationship emerged between monocyte chemoattractant protein-1 (MCP-1) and sepsis-induced mortality. Conversely, elevated macrophage inflammatory protein 1 beta (MIP1B) concentrations were positively linked with both sepsis incidence and associated mortality. These revelations underscore the causal impact of certain circulating cytokines on sepsis susceptibility and its prognosis, hinting at the therapeutic potential of modulating these cytokine levels. Additional research is essential to corroborate these connections.
Tyrosine phosphatase PTPN11/SHP2 in solid tumors - bull’s eye for targeted therapy?
Authors: Chen Xun , Keller Steffen Johannes , Hafner Philipp , Alrawashdeh Asma Y. , Avery Thomas Yul , Norona Johana , Zhou Jinxue , Ruess Dietrich Alexander
Published: March 2024

Encoded by PTPN11, the Src-homology 2 domain-containing phosphatase 2 (SHP2) integrates signals from various membrane-bound receptors such as receptor tyrosine kinases (RTKs), cytokine and integrin receptors and thereby promotes cell survival and proliferation. Activating mutations in the PTPN11 gene may trigger signaling pathways leading to the development of hematological malignancies, but are rarely found in solid tumors. Yet, aberrant SHP2 expression or activation has implications in the development, progression and metastasis of many solid tumor entities. SHP2 is involved in multiple signaling cascades, including the RAS-RAF-MEK-ERK-, PI3K-AKT-, JAK-STAT- and PD-L1/PD-1- pathways. Although not mutated, activation or functional requirement of SHP2 appears to play a relevant and context-dependent dichotomous role. This mostly tumor-promoting and infrequently tumor-suppressive role exists in many cancers such as gastrointestinal tumors, pancreatic, liver and lung cancer, gynecological entities, head and neck cancers, prostate cancer, glioblastoma and melanoma. Recent studies have identified SHP2 as a potential biomarker for the prognosis of some solid tumors. Based on promising preclinical work and the advent of orally available allosteric SHP2-inhibitors early clinical trials are currently investigating SHP2-directed approaches in various solid tumors, either as a single agent or in combination regimes. We here provide a brief overview of the molecular functions of SHP2 and collate current knowledge with regard to the significance of SHP2 expression and function in different solid tumor entities, including cells in their microenvironment, immune escape and therapy resistance. In the context of the present landscape of clinical trials with allosteric SHP2-inhibitors we discuss the multitude of opportunities but also limitations of a strategy targeting this non-receptor protein tyrosine phosphatase for treatment of solid tumors.
Case report: A case of novel homozygous LRBA variant induced by chromosomal segmental uniparental disomy - genetic and clinical insights
Authors: Jiang Lihua , Chen Sen
Published: March 2024

Objective

The study aims to report a rare case of a novel homozygous variant in the LRBA gene, originating from uniparental disomy of paternal origin. This case contributes new clinical data to the LRBA gene variant database.

Methods

The study details the case of a 2-year-old child diagnosed in May 2023 at our center with a homozygous LRBA gene variant. Detailed clinical data of the patient were collected, including whole-exome sequencing of peripheral blood mononuclear cells, with parental genetic verification.

Results

The child presented with recurrent respiratory infections and chronic neutropenia, progressing to pancytopenia. Imaging showed splenomegaly and enlarged lymph nodes in the axillary and abdominal regions. Peripheral blood lymphocyte count revealed reduced B cells and NK cells. Elevated cytokine levels of IFN-α and IFN-r were observed. Whole-exome sequencing revealed a nonsense homozygous variant in the LRBA gene, specifically c.2584C>T (p.Gln862Ter). The father exhibited a heterozygous variant at this locus, while no variant was found in the mother. Sample analysis indicated characteristics of uniparental disomy. According to the guidelines of the American College of Medical Genetics and Genomics (ACMG), this variant is preliminarily classified as “Likely pathogenic”. Currently, there are no reports in academic literature regarding this specific variant site.

Conclusion

LRBA gene variants can lead to a rare inborn error of immunity disease. The c.2584C>T (p.Gln862Ter) variant in exon 22 of the LRBA gene is a newly identified pathogenic variant, and the homozygous variant caused by uniparental disomy is exceedingly rare. This case represents the second global report of an LRBA gene function loss due to uniparental disomy abnormalities.
Perspective on intestinal microbiota temporal changes of herbal additives treated shrimp in a natural aquaculture setting
Authors: Lin Xu-Yin , Shih Yi-Jia , Zhang Xian-Jing , Cai You-Shu , Zhou Xiao-Wen , Chen Jung-Sheng
Published: March 2024

Shrimp is an important aquaculture species worldwide. The use of antibiotics to suppress disease outbreaks has led to antibiotic resistance; however, probiotics or natural herbal additives can enhance the health of farmed shrimp. In this study, the effects of formulations containing natural herbs and probiotics on shrimp farming were explored. Following indoor shrimp farming, the shrimp were returned to outdoor natural ponds for 1 week in the presence of a fermented probiotic product. The gut microbiota was surveyed using 16S rRNA gene sequencing at 1, 2, 3, and 8 weeks after the natural pond release. The results showed that Vibrio-related bacterial genera increased significantly in the shrimp intestinal microbiota at 2 weeks and were particularly high at 3 weeks after natural pond release. The phyla Firmicutes, Bacteroidetes, Vibrio-related bacteria, and the genus Cetobacterium emerged as crucial bacteria linked to shrimp health and growth. Overall, the diversity of the shrimp intestinal microbiota was lower upon release into the natural pond. However, this outcome may be associated with dysbiosis or influenced by the natural environment. Further research is warranted to substantiate these findings. A perspective on the shrimp gut microbiota provides important information for aquaculture management and explains the implementation of control measures.
Development and validation of a predictive model for stroke associated pneumonia in patients after thrombectomy for acute ischemic stroke
Authors: Wang Jingying , Yang Chao , Zhang Ruihai , Hu Wei , Yang Peng , Jiang Yiqing , Hong Weijun , Shan Renfei , Jiang Yongpo
Published: March 2024

Objective

This study aims to identify the risk factors associated with stroke-associated pneumonia (SAP) in patients who have undergone thrombectomy for acute ischemic stroke and to develop a nomogram chart model for predicting the occurrence of pneumonia.

Methods

Consecutive patients who underwent thrombectomy for acute ischemic stroke were enrolled from three hospitals at Taizhou Enze Medical Center. They were randomly divided into a training group and a validation group in a 7:3 ratio. The training group data was used to screen for effective predictive factors using LASSO regression. Multiple logistic regression was then conducted to determine the predictive factors and construct a nomogram chart. The model was evaluated using the validation group, analyzing its discrimination, calibration, and clinical decision curve. Finally, the newly constructed model was compared with the AIS-APS, A2DS2, ISAN, and PANTHERIS scores for acute ischemic stroke-associated pneumonia.

Results

Out of 913 patients who underwent thrombectomy, 762 were included for analysis, consisting of 473 males and 289 females. The incidence rate of SAP was 45.8%. The new predictive model was constructed based on three main influencing factors: NIHSS ≥16, postoperative LMR, and difficulty swallowing. The model demonstrated good discrimination and calibration. When applying the nomogram chart to threshold probabilities between 7 and 90%, net returns were increased. Furthermore, the AUC was higher compared to other scoring systems.

Conclusion

The constructed nomogram chart in this study outperformed the AIS-APS, A2DS2 score, ISAN score, and PANTHERIS score in predicting the risk of stroke-associated pneumonia in patients with acute ischemic stroke after thrombectomy. It can be utilized for clinical risk prediction of stroke-associated pneumonia in patients after thrombectomy for acute ischemic stroke.
Robotic surgery for deep-infiltrating endometriosis: is it time to take a step forward?
Authors: Ferrari Filippo Alberto , Youssef Youssef , Naem Antoine , Ferrari Federico , Odicino Franco , Krentel Harald , Moawad Gaby
Published: March 2024

Endometriosis is a chronic debilitating disease that affects nearly 10% of women of the reproductive age. Although the treatment modalities of endometriosis are numerous, surgical excision of the endometriotic implants and nodules remains the sole cytoreductive approach. Laparoscopic excision of endometriosis was proven to be beneficial in improving the postoperative pain and fertility. Moreover, it was also proved to be safe and efficient in treating the visceral localization of deep endometriosis, such as urinary and colorectal endometriosis. More recently, robotic-assisted surgery gained attention in the field of endometriosis surgery. Although the robotic technology provides a 3D vision of the surgical field and 7-degree of freedom motion, the safety, efficacy, and cost-effectiveness of this approach are yet to be determined. With this paper, we aim to review the available evidence regarding the role of robotic surgery in the management of endometriosis along with the current practices in the field.
Unravelling the synergistic interaction of Thrips tabaci and newly recorded, Thrips parvispinus with Alternaria porri (Ellis.) Cif., inciting onion purple blotch
Authors: Saini Shubham , Raj Kushal , Saini Anil Kumar , Kumar Rakesh , Saini Ankit , Khan Aslam , Kumar Pankaj , Devi Geeta , Bhambhu Mukul Kumar , McKenzie Cindy L. , Lal Makhan , Wati Leela
Published: March 2024

Onion purple blotch is the most indispensable foliar disease of crop and has become a major concern for farmers and research fraternity. An attempt to investigate the role of injury in parasitism by Alternaria porri indicated that disease incidence and severity enhance considerably with injury. Thrips injured plants inoculated with A. porri presented 100% incidence and 52–72% severity while mechanically injured plants inoculated with A. porri showed 60–70% incidence and 28–34% severity. The uninjured plants showed considerably less disease incidence (30–40%) and severity (10–16%). Injured inoculated plants presented reduced leaf length and leaf area while the leaf diameter remained unaffected. The lesion number, lesion length and size was substantially enhanced with concomitant infestation of pest and pathogen. Thrips tabaci injury led to more pronounced symptoms of purple blotch compared to Thrips parvispinus injury. There was substantial decrease in photosynthetic rate and chlorophyll content with stress imposed on plant whilst the relative stress injury was enhanced. The induction of injury and inoculation of A. porri had an impact on the concentration of total phenolics, total soluble sugars, total proteins and hydrogen peroxide in onion leaves. A. porri combined with injury caused a more pronounced decrease in total soluble sugars and total protein content while enhancement in total phenolics and hydrogen peroxide content compared to uninjured plants. The dynamic nature of morpho-physiological and biochemical changes owing to stress conditions imposed on onion plant adds an extra layer of complexity in understanding the onion plant physiology and their ability to work out in response to challenging environment conditions.
Metabolites: a converging node of host and microbe to explain meta-organism
Authors: Chakraborty Nabarun
Published: March 2024

Meta-organisms encompassing the host and resident microbiota play a significant role in combatting diseases and responding to stress. Hence, there is growing traction to build a knowledge base about this ecosystem, particularly to characterize the bidirectional relationship between the host and microbiota. In this context, metabolomics has emerged as the major converging node of this entire ecosystem. Systematic comprehension of this resourceful omics component can elucidate the organism-specific response trajectory and the communication grid across the ecosystem embodying meta-organisms. Translating this knowledge into designing nutraceuticals and next-generation therapy are ongoing. Its major hindrance is a significant knowledge gap about the underlying mechanisms maintaining a delicate balance within this ecosystem. To bridge this knowledge gap, a holistic picture of the available information has been presented with a primary focus on the microbiota-metabolite relationship dynamics. The central theme of this article is the gut-brain axis and the participating microbial metabolites that impact cerebral functions.
An operating principle of the cerebral cortex, and a cellular mechanism for attentional trial-and-error pattern learning and useful classification extraction
Authors: Rvachev Marat M.
Published: March 2024

A feature of the brains of intelligent animals is the ability to learn to respond to an ensemble of active neuronal inputs with a behaviorally appropriate ensemble of active neuronal outputs. Previously, a hypothesis was proposed on how this mechanism is implemented at the cellular level within the neocortical pyramidal neuron: the apical tuft or perisomatic inputs initiate “guess” neuron firings, while the basal dendrites identify input patterns based on excited synaptic clusters, with the cluster excitation strength adjusted based on reward feedback. This simple mechanism allows neurons to learn to classify their inputs in a surprisingly intelligent manner. Here, we revise and extend this hypothesis. We modify synaptic plasticity rules to align with behavioral time scale synaptic plasticity (BTSP) observed in hippocampal area CA1, making the framework more biophysically and behaviorally plausible. The neurons for the guess firings are selected in a voluntary manner via feedback connections to apical tufts in the neocortical layer 1, leading to dendritic Ca2+ spikes with burst firing, which are postulated to be neural correlates of attentional, aware processing. Once learned, the neuronal input classification is executed without voluntary or conscious control, enabling hierarchical incremental learning of classifications that is effective in our inherently classifiable world. In addition to voluntary, we propose that pyramidal neuron burst firing can be involuntary, also initiated via apical tuft inputs, drawing attention toward important cues such as novelty and noxious stimuli. We classify the excitations of neocortical pyramidal neurons into four categories based on their excitation pathway: attentional versus automatic and voluntary/acquired versus involuntary. Additionally, we hypothesize that dendrites within pyramidal neuron minicolumn bundles are coupled via depolarization cross-induction, enabling minicolumn functions such as the creation of powerful hierarchical “hyperneurons” and the internal representation of the external world. We suggest building blocks to extend the microcircuit theory to network-level processing, which, interestingly, yields variants resembling the artificial neural networks currently in use. On a more speculative note, we conjecture that principles of intelligence in universes governed by certain types of physical laws might resemble ours.
Applications of multiphoton microscopy in imaging cerebral and retinal organoids
Authors: Lacin Macit Emre , Yildirim Murat
Published: March 2024

Cerebral organoids, self-organizing structures with increased cellular diversity and longevity, have addressed shortcomings in mimicking human brain complexity and architecture. However, imaging intact organoids poses challenges due to size, cellular density, and light-scattering properties. Traditional one-photon microscopy faces limitations in resolution and contrast, especially for deep regions. Here, we first discuss the fundamentals of multiphoton microscopy (MPM) as a promising alternative, leveraging non-linear fluorophore excitation and longer wavelengths for improved imaging of live cerebral organoids. Then, we review recent applications of MPM in studying morphogenesis and differentiation, emphasizing its potential for overcoming limitations associated with other imaging techniques. Furthermore, our paper underscores the crucial role of cerebral organoids in providing insights into human-specific neurodevelopmental processes and neurological disorders, addressing the scarcity of human brain tissue for translational neuroscience. Ultimately, we envision using multimodal multiphoton microscopy for longitudinal imaging of intact cerebral organoids, propelling advancements in our understanding of neurodevelopment and related disorders.
Identifying factors that indicate the possibility of non-visible cases on mammograms using mammary gland content ratio estimated by artificial intelligence
Authors: Kai Chiharu , Otsuka Tsunehiro , Nara Miyako , Kondo Satoshi , Futamura Hitoshi , Kodama Naoki , Kasai Satoshi
Published: March 2024

Background

Mammography is the modality of choice for breast cancer screening. However, some cases of breast cancer have been diagnosed through ultrasonography alone with no or benign findings on mammography (hereby referred to as non-visibles). Therefore, this study aimed to identify factors that indicate the possibility of non-visibles based on the mammary gland content ratio estimated using artificial intelligence (AI) by patient age and compressed breast thickness (CBT).

Methods

We used AI previously developed by us to estimate the mammary gland content ratio and quantitatively analyze 26,232 controls and 150 non-visibles. First, we evaluated divergence trends between controls and non-visibles based on the average estimated mammary gland content ratio to ensure the importance of analysis by age and CBT. Next, we evaluated the possibility that mammary gland content ratio ≥50% groups affect the divergence between controls and non-visibles to specifically identify factors that indicate the possibility of non-visibles. The images were classified into two groups for the estimated mammary gland content ratios with a threshold of 50%, and logistic regression analysis was performed between controls and non-visibles.

Results

The average estimated mammary gland content ratio was significantly higher in non-visibles than in controls when the overall sample, the patient age was ≥40 years and the CBT was ≥40 mm (p < 0.05). The differences in the average estimated mammary gland content ratios in the controls and non-visibles for the overall sample was 7.54%, the differences in patients aged 40–49, 50–59, and ≥60 years were 6.20%, 7.48%, and 4.78%, respectively, and the differences in those with a CBT of 40–49, 50–59, and ≥60 mm were 6.67%, 9.71%, and 16.13%, respectively. In evaluating mammary gland content ratio ≥50% groups, we also found positive correlations for non-visibles when controls were used as the baseline for the overall sample, in patients aged 40–59 years, and in those with a CBT ≥40 mm (p < 0.05). The corresponding odds ratios were ≥2.20, with a maximum value of 4.36.

Conclusion

The study findings highlight an estimated mammary gland content ratio of ≥50% in patients aged 40–59 years or in those with ≥40 mm CBT could be indicative factors for non-visibles.
Case report: Dissolving carotid plaque associated to Lorlatinib-related dyslipidemia
Authors: Mayer-Suess Lukas , Knoflach Michael , Pircher Andreas , Kiechl Stefan , Schmidauer Christoph , Hametner Eva
Published: March 2024

We present a case with prolonged Lorlatinib-related dyslipidemia causing internal carotid artery stenosis, putting the patient at risk of cerebrovascular events. Through intensified lipid-lowering treatment and dose reduction of Lorlatinib, LDL-C levels decreased markedly. Surprisingly, the left sided internal carotid artery stenosis dissolved accordingly. Due to the high efficacy of the new selective tyrosine kinase inhibitors and resulting long-term treatment, it is essential to carefully follow-up and include drug specific side effect monitoring. This case emphasizes that Loraltinib-related dyslipidemia has to be taken seriously and treatment should be initiated as promptly as possible. We conclude that in cases were lipid dysregulation remains and Lorlatinib treatment has to be continued, cerebrovascular appraisal through ultrasound should be considered and, if stenosis is evident, intensified treatment regimen of dyslipidemia or dose reduction of Lorlatinib should be discussed in an interdisciplinary setting.
An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization
Authors: Awais Muhammad , Abdal Md. Nazmul , Akram Tallha , Alasiry Areej , Marzougui Mehrez , Masood Anum
Published: March 2024

In the field of medicine, decision support systems play a crucial role by harnessing cutting-edge technology and data analysis to assist doctors in disease diagnosis and treatment. Leukemia is a malignancy that emerges from the uncontrolled growth of immature white blood cells within the human body. An accurate and prompt diagnosis of leukemia is desired due to its swift progression to distant parts of the body. Acute lymphoblastic leukemia (ALL) is an aggressive type of leukemia that affects both children and adults. Computer vision-based identification of leukemia is challenging due to structural irregularities and morphological similarities of blood entities. Deep neural networks have shown promise in extracting valuable information from image datasets, but they have high computational costs due to their extensive feature sets. This work presents an efficient pipeline for binary and subtype classification of acute lymphoblastic leukemia. The proposed method first unveils a novel neighborhood pixel transformation method using differential evolution to improve the clarity and discriminability of blood cell images for better analysis. Next, a hybrid feature extraction approach is presented leveraging transfer learning from selected deep neural network models, InceptionV3 and DenseNet201, to extract comprehensive feature sets. To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. These optimized features subsequently empower multiple classifiers, potentially capturing diverse perspectives and amplifying classification accuracy. The proposed pipeline is validated on publicly available standard datasets of ALL images. For binary classification, the best average accuracy of 98.1% is achieved with 98.1% sensitivity and 98% precision. For ALL subtype classifications, the best accuracy of 98.14% was attained with 78.5% sensitivity and 98% precision. The proposed feature selection method shows a better convergence behavior as compared to classical population-based meta-heuristics. The suggested solution also demonstrates comparable or better performance in comparison to several existing techniques.
Ferroptosis in hepatocellular carcinoma, from mechanism to effect
Authors: Jiang Shuang , Zhang Guangcong , Ma Yanan , Wu Dongyu , Xie Da , Zhou Songke , Jiang Xuemei
Published: March 2024

Hepatocellular carcinoma (HCC) is a prevalent malignant tumor worldwide, characterized by high malignancy and rapid progression. Most cases are diagnosed at intermediate to advanced stages. Current treatment methods have limited efficacy, resulting in high recurrence rates and poor prognosis. Radical hepatectomy remains the primary treatment for HCC, complemented by radiotherapy, chemotherapy, targeted therapy, and immunotherapy. Despite significant improvement in patient prognosis with radical hepatectomy, the five-year survival rate post-surgery remains low; thus necessitating exploration of more effective therapeutic approaches. Ferroptosis is a recently discovered form of cell death that can modulate the occurrence and development of HCC through various mechanisms. This article aims to elucidate the mechanism of ferroptosis and its impact on HCC development to provide novel insights for diagnosis and treatment.