bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of cement ring sealing under cyclic loading conditions
Authors: Zhang Yuhao
Published: November 2024

As exploration and development continue to advance, incidents of cement ring seal failures are occurring more frequently. Such failures can directly impact the safe development of oil and gas wells. To effectively assess the sealing performance of cement rings, this paper explores the mechanisms behind sealing failures at both the cementing interface and the cement ring body under cyclic loading conditions. It also examines the sealing capabilities of the initial cementing interface and the cement ring body by developing a finite element model of the ‘casing-cement ring-facility’ and incorporating the Cohesive cementing unit. The findings indicate that the pressure within the casing is extremely high, and the cement ring is tightly sealed. The results indicate that fluctuations in pressure within the casing can compromise the sealing effectiveness of the cement ring, leading to micro-annular gaps at either the first or second cementing interface. Additionally, damage to the Cohesive unit initiates during the first loading cycle, with increased displacement of the initial cement surface correlating to higher pressure cycles.
Underwater acoustic target recognition model based on transformer and knowledge distillation
Authors: Yu Beiming , Chen Yuechao , Du Shuanping , Bian Zhenwei
Published: November 2024

Traditional methods for feature extraction in underwater acoustics heavily rely on domain expertise and handcrafted features, which are often challenged by the complex and variable ocean environment. In contrast, deep learning models, particularly those based on CNNs and Transformers, offer significant advantages in automatic feature extraction and classification tasks. This study introduces a Spectrogram-Vision Transformer (SViT) model, specifically designed for spectrogram classification, leveraging pre-trained Vision Transformer (ViT) models. The SViT model is further utilized as a teacher model in a knowledge distillation framework, where its robust feature extraction capabilities are transferred to a lightweight ResNet50 student model. Experimental results on the DeepShip dataset demonstrate that the proposed method significantly improves the recognition accuracy and generalization capability of ResNet50, achieving performance close to the more computationally intensive SViT model. This research highlights the effectiveness of Transformers in underwater target recognition and underscores the potential of knowledge distillation in enhancing the performance of lightweight models for real-world applications, particularly in resource-constrained environments.
Improved black-winged kite algorithm based on chaotic mapping and adversarial learning
Authors: Zhao Mingjing , Su Zhongji , Zhao Chenyang , Hua Zexi
Published: November 2024

Aiming at the shortcomings of the black-winged kite algorithm, such as poor uniformity of initial population distribution, subjective search and single direction, this paper proposes an improved black-winged kite algorithm based on chaotic mapping and adversarial learning. It then progresses to adopting Tent chaotic mapping to achieve a uniform initial solution distribution, introducing Beta random distribution and optimizing the nonlinear factor in the attack phase to make the search trend more in line with the demand, and introducing an adversarial learning mechanism to extend the search direction. Twelve benchmark test functions are tested and compared with five other algorithms, and the result shows that the algorithm significantly outperforms the other algorithms in terms of searching ability and optimization-finding accuracy.
A variable step and multi-constraint vehicle’s trajectory generation algorithm based on deep deterministic policy gradient network
Authors: Hu Xingzhi , Li Mingjie , Zhao Bendong , Wang Zhiren , Lai Jianqi
Published: November 2024

Aiming at the problem that the traditional vehicle’s trajectory generation method takes a long time and is difficult to calculate in real time, a variable step and multi-constraint trajectory generation algorithm based on a deep deterministic policy gradient (DDPG) network is proposed. Firstly, the dynamic model and constraint conditions of the vehicle are analyzed. On this basis, the reinforcement learning training model is constructed based on DDPG, and the state, action, and reward design of the training model are defined. At the same time, the variable step is introduced into the action model to improve the generated trajectory’s navigation precision. Finally, the proposed method is verified under different cases, and according to the results, the proposed method can realize quick generation of multi-constraint guidance trajectories.
W-system: A system to understand words in Wordle
Authors: Yang Qiaochu
Published: November 2024

Wordle is a popular puzzle game where players share their daily scores on Twitter. Based on this data, we developed a W-system to analyze and predict Wordle game outcomes, providing insights for further game development. The number of reported results varies daily. To explain this variation, we first cleaned the data reported on Twitter and performed autocorrelation and ADF tests, revealing that the series was not stationary. After performing first-order differencing, we confirmed stationarity. Using the AIC criterion, we determined that the ARIMA (1, 1, 0) model was optimal. We performed residual and LB tests, and then predicted the number of reports for the next 60 days, identifying a decreasing trend. Additionally, we investigated whether any attributes of the words affected the percentage of scores reported in Hard Mode using a random forest model. We found that certain vowels, such as A and E, made words easier, while I and O made words harder. To predict the distribution of reported results for a given future solution word, we designed a 24-5-7 fully connected neural network. The input layer consists of a 24-dimensional vector representing letter occurrences, the hidden layer has five neurons, and the output layer is a 7-dimensional vector representing the distribution of scores. We trained the model using MSE error and the Adam optimizer, achieving a final test set loss of 7.22, indicating good generalization ability. For example, for the word EERIE on March 1, 2023, the model predicted distribution with reasonable confidence, accounting for associated uncertainties. We also developed a model to classify solution words by difficulty. We identified eight attributes of words and used the Analytic Hierarchy Process (AHP) to assign weights to each feature. Applying the k-means clustering algorithm, we classified 355 words into three categories: easy, medium, and hard. Using our model, the word EERIE was classified as medium difficulty. We validated our model by plotting a two-dimensional clustering scatter plot using the two features with the highest weights, showing good separation among the three categories, and indicating the accuracy of our classification model.
Integration of storage in depleted gas reservoirs evaluation of injection and extraction operation
Authors: Ai Xingbo , Zhou Ziyu , ZhaoYang
Published: November 2024

In order to accurately evaluate the operation status of gas injection and production in reservoirs with depleted volcanic reservoirs and the injection and production capacity of a single well, an integrated model of the pore reservoir - wellbore - surface pipeline network was established for the Xushen gas field. Besides, the optimization algorithm of the integrated simulation was used to set up the optimization objective function according to the needs of the actual study, to build the optimization control variables at each level of the system, and to set up single-well production conditions under several additional constraints, including full production capacity, water/gas ratio, fluid-carrying capacity, and peak/valley production changes. The production conditions of a single well are set by the calculation of each sub-system and additional requirements in the field. Through the optimization calculation, the production distribution of a single well is obtained under the conditions of giving full play to the production capacity, taking into account the water/gas ratio, the liquid-carrying capacity, and the production changes during peak and valley periods. The study shows that the water intrusion volume of alternating injection and extraction exhibits cyclic changes of alternating increase and decrease, and the numerical simulation method of the gas reservoir predicts that the water intrusion volume of the scenario at the end of multi-cycle gas injection is 260-340×104 m^3, and that of the scenario at the end of multi-cycle gas extraction is 550-610×104 m^3; and that of the straight well scenario is larger, with a single-cycle volume of 289-338×104 m^3 at the late stage of the five rounds of injection and extraction cycles; The horizontal well program has a larger water intrusion amount, with a single-cycle water intrusion amount of 289-338×104 m^3 at the end of five injection and extraction cycles.
Improved current control strategies for LCL grid-connected inverters for weak grids
Authors: Feng Jianxiang , Zhang Jihong
Published: November 2024

With the continuous progress of new energy technology, the application of LCL-type grid-connected inverters is becoming more and more widespread. However, these inverters have harmonic and stability problems during the grid-connection process. Especially when the grid impedance is large, their quality and safety are easily affected. Therefore, in this study, an improved current control strategy is proposed to solve the above problems. In this study, the first important task is to establish an accurate mathematical model, which takes into account the special characteristics of weak grids and the dynamic behavior of LCL filters. On this basis, the shortcomings of the traditional control strategy are analyzed and targeted improvement measures are proposed, including a control method based on phase compensation and a fuzzy control filter design. The current control strategy reduces the external disturbance and improves the system stability by controlling the current according to the magnitude of the disturbance effect after the disturbance is generated and before the controlled variable changes.
The data acquisition system of phenoPET
Authors: Streun M. , Eguzo C. , Gorke H. , Heil R. , Hinz C. , Keßel D. , Koller R. , Metzner R. , Pflugfelder D. , Scheins J. , Scherer B. , Wüstner P. , van Waasen S.
Published: November 2024

The PET scanner phenoPET is a system dedicated for plant research developed and used for phenotyping studies at the Research Center in Jülich.
The detectors consist of LYSO scintillators and Philips digital silicon photomultipliers.
A central processing board collects their data and transfers them through a USB-3 connection to the data acquisition server.
The USB-3 restricts the maximum output rate to 380 MB/s, which requires controlled data dropping on the board in order to allow measurements with activities that would exceed this limit.
Presently we are developing a new readout system that will eliminate this bottleneck.
We will replace the USB-3 by a fiber optics link with a maximum data rate of 2 GB/s.
In addition, the new central board will provide an embedded operation system (PetaLinux) that has direct access to the hardware interfaces for configuration and monitoring of the detector modules.
This will allow the control software to run directly on the board.
Broad-band, high-gain, low-frequency antennas for radio detection of earth-skimming tau neutrinos
Authors: Huege T. , Krömer O.
Published: November 2024

A promising approach to detect high-energy tau neutrinos is
through the measurement of impulsive radio emission from horizontal
air showers initiated in the Earth's atmosphere. Observations at
frequencies between 30 and 80 MHz seem particularly promising —
if high-gain antennas focused at the horizon and blocking out as
much as possible of the noisy sky are employed. Due to the large
wavelengths, however, designing an antenna with the required
properties is highly non-trivial at such low frequencies. In this
article, we explore suitable antenna designs that provide the
desired high gain, possess a smooth beam, are insensitive to ground
conditions, are easily impedance-matched over the wide band, and are
mechanically simple for deployment in large numbers in inaccessible
terrain. In particular, we consider the “rhombus” antenna design
for both horizontally and vertically polarized radiation a very
attractive option for tau neutrino detection efforts in the
atmosphere with the radio technique.
Sodium alginate based fast swelling nanogels for solubility enhancement of chlorthalidone; synthesis, characterization and biosafety evaluation
Authors: Badshah Syed Faisal , Abdullah Orva , Khan Kifayat Ullah , Hussain Abid , Mukhtiar Muhammad , Barkat Kashif , Jan Nasrullah , Khan Samiullah , Aamir Muhammad , Liaqat Huma , Mehmood Yasir , Jabbar Abdul , Waqar Maham , Khanum Tehreem
Published: November 2024

Purpose of the study was to enhance the solubility of chlorthalidone, poorly soluble diuretic that has been the used for lowering high blood pressure for the past half-century. Solubility is a challenge for approximately 90% of drug candidates. Chlorthalidone is BCS Class IV drug whose poor solubility needs to be improved in order to optimize its efficacy. Using a free radical polymerization technique, sodium alginate-based nanogels were formulated for enhancing solubility of chlorthalidone. The evaluation of various characteristics of nanogels was done by structural characterization, drug loading, swelling, sol–gel transition, in-vitro release, solubility, and toxicity tests. Fourier transform infrared (FT-IR) spectroscopy revealed characteristic peaks of the primary raw materials and polymeric nanogels. The FT-IR spectra of the chlorthalidone-loaded nanogels suggested discrete drug peaks confirming successful drug loading. The system’s amorphous nature and thermal stability were indicated by powder x-ray diffractometry and thermal analysis. The scanning electron microscopy indicated a well-defined porous structure. The size of the nanogels was determined by zeta size analysis to be 189 ± 18.35 n·m. The solubility enhancement factor demonstrated the potential for improved solubility of the poorly soluble drug. The resulting biocompatible nanogels could be used to improve the solubility of hydrophobic drugs.
Interactive effects between extreme temperatures and PM2.5 on cause-specific mortality in thirteen U.S. states
Authors: Castro Edgar , Healy James , Liu Abbie , Wei Yaguang , Kosheleva Anna , Schwartz Joel
Published: November 2024

The extent and robustness of the interaction between exposures to heat and ambient PM2.5 is unclear and little is known of the interaction between exposures to cold and ambient PM2.5. Clarifying these interactions, if any, is crucial due to the omnipresence of PM2.5 in the atmosphere and increasing scope and frequency of extreme temperature events. To investigate both of these interactions, we merged 6 073 575 individual-level mortality records from thirteen states spanning seventeen years with 1 km daily PM2.5 predictions from sophisticated prediction model and 1 km meteorology from Daymet V4. A time-stratified, bidirectional case-crossover design was used to control for confounding by individual-level, long-term and cyclic weekly characteristics. We fitted conditional logistic regressions with an interaction term between PM2.5 and extreme temperature events to investigate the potential interactive effects on mortality. Ambient PM2.5 exposure has the greatest effect on mortality by all internal causes in the 2 d moving average exposure window. Additionally, we found consistently synergistic interactions between a 10 μg m−3 increase in the 2 d moving average of PM2.5 and extreme heat with interaction odds ratios of 1.013 (95% CI: 1.000, 1.026), 1.024 (95% CI: 1.002, 1.046), and 1.033 (95% CI: 0.991, 1.077) for deaths by all internal causes, circulatory causes, and respiratory causes, respectively, which represent 75%, 156%, and 214% increases in the coefficient estimates for PM2.5 on those days. We also found evidence of interactions on the additive scale with corresponding relative excess risks due to interaction (RERIs) of 0.013 (95% CI: 0.003, 0.021), 0.020 (95% CI: 0.008, 0.031), and 0.017 (95% CI: −0.015, 0.036). Interactions with other PM2.5 exposure windows were more pronounced. For extreme cold, our results were suggestive of an antagonistic relationship. These results suggest that ambient PM2.5 interacts synergistically with exposure to extreme heat, yielding greater risks for mortality than only either exposure alone.
Manufacturing of lithium battery toward deep-sea environment
Authors: Zhao Yaohua , Li Nan , Xie Keyu , Wang Chuan , Zhou Sisi , Zhang Xianggong , Ye Cong
Published: November 2024

The operation of deep-sea underwater vehicles relies entirely on onboard batteries. However, the extreme deep-sea conditions, characterized by ultrahigh hydraulic pressure, low temperature, and seawater conductivity, pose significant challenges for battery development. These conditions drive the need for specialized designs in deep-sea batteries, incorporating critical aspects of power generation, protection, distribution, and management. Over time, deep-sea battery technology has evolved through multiple generations, with lithium (Li) batteries emerging in recent decades as the preferred power source due to their high energy and reduced operational risks. Although the rapid progress of Li batteries has notably advanced the capabilities of underwater vehicles, critical technical issues remain unresolved. This review first systematically presents the whole picture of deep-sea battery manufacturing, focusing on Li batteries as the current mainstream solution for underwater power. It examines the key aspects of deep-sea Li battery development, including materials selection informed by electro-chemo-mechanics models, component modification and testing, and battery management systems specialized in software and hardware. Finally, it discusses the main challenges limiting the utilization of deep-sea batteries and outlines promising directions for future development. Based on the systematic reflection on deep-sea batteries and discussion on deep-sea Li batteries, this review aims to provide a research foundation for developing underwater power tailored for extreme environmental exploration.
A data-driven compact drain current model for InGaAs FinFET using TCAD assisted machine learning approach
Authors: Maity Arya , Kumar Maity Subir , Das Himadri Sekhar
Published: November 2024

This article presents a novel machine learning-based framework for modeling the drain current of InGaAs FinFETs. An artificial neural network, trained on a comprehensive dataset generated by 3D numerical device simulations, forms the core of this model. The simulations covered a wide range of device geometries and bias conditions, resulting in diverse current-voltage characteristics. Using TensorFlow in a Python environment, we built and trained a neural network to accurately predict drain current. The model's performance was evaluated on independent test datasets, demonstrating its effectiveness on unseen data. The model accurately captures the effects of varying gate length, drain voltage, and gate voltage. Multiple error metrics, including mean squared error, mean absolute error, root mean squared error, and correlation coefficient, were used to assess its performance. At shorter gate lengths, the calculated relative error in drain current was 2.18% and 1.17% at V

DS
= 50mV and 1V, respectively. After training, the network parameters were extracted to create a Verilog-A model. This model was integrated into the SPICE simulator for circuit simulations. A resistive load inverter circuit was designed to demonstrate the model's capabilities, and voltage transfer characteristics and transient analysis were performed within SPICE. These results validate the effectiveness of the developed machine learning-based InGaAs FinFET model.
DiMA: sequence diversity dynamics analyser for viruses
Authors: Tharanga Shan , Ünlü Eyyüb Selim , Hu Yongli , Sjaugi Muhammad Farhan , Çelik Muhammet A , Hekimoğlu Hilal , Miotto Olivo , Öncel Muhammed Miran , Khan Asif M
Published: November 2024

Sequence diversity is one of the major challenges in the design of diagnostic, prophylactic, and therapeutic interventions against viruses. DiMA is a novel tool that is big data-ready and designed to facilitate the dissection of sequence diversity dynamics for viruses. DiMA stands out from other diversity analysis tools by offering various unique features. DiMA provides a quantitative overview of sequence (DNA/RNA/protein) diversity by use of Shannon’s entropy corrected for size bias, applied via a user-defined k-mer sliding window to an input alignment file, and each k-mer position is dissected to various diversity motifs. The motifs are defined based on the probability of distinct sequences at a given k-mer alignment position, whereby an index is the predominant sequence, while all the others are (total) variants to the index. The total variants are sub-classified into the major (most common) variant, minor variants (occurring more than once and of incidence lower than the major), and the unique (singleton) variants. DiMA allows user-defined, sequence metadata enrichment for analyses of the motifs. The application of DiMA was demonstrated for the alignment data of the relatively conserved Spike protein (2,106,985 sequences) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the relatively highly diverse pol gene (2637) of the human immunodeficiency virus-1 (HIV-1). The tool is publicly available as a web server (https://dima.bezmialem.edu.tr), as a Python library (via PyPi) and as a command line client (via GitHub).
FunlncModel: integrating multi-omic features from upstream and downstream regulatory networks into a machine learning framework to identify functional lncRNAs
Authors: Li Yan-Yu , Qian Feng-Cui , Zhang Guo-Rui , Li Xue-Cang , Zhou Li-Wei , Yu Zheng-Min , Liu Wei , Wang Qiu-Yu , Li Chun-Quan
Published: November 2024

Accumulating evidence indicates that long noncoding RNAs (lncRNAs) play important roles in molecular and cellular biology. Although many algorithms have been developed to reveal their associations with complex diseases by using downstream targets, the upstream (epi)genetic regulatory information has not been sufficiently leveraged to predict the function of lncRNAs in various biological processes. Therefore, we present FunlncModel, a machine learning–based interpretable computational framework, which aims to screen out functional lncRNAs by integrating a large number of (epi)genetic features and functional genomic features from their upstream/downstream multi-omic regulatory networks. We adopted the random forest method to mine nearly 60 features in three categories from >2000 datasets across 11 data types, including transcription factors (TFs), histone modifications, typical enhancers, super-enhancers, methylation sites, and mRNAs. FunlncModel outperformed alternative methods for classification performance in human embryonic stem cell (hESC) (0.95 Area Under Curve (AUROC) and 0.97 Area Under the Precision-Recall Curve (AUPRC)). It could not only infer the most known lncRNAs that influence the states of stem cells, but also discover novel high-confidence functional lncRNAs. We extensively validated FunlncModel’s efficacy by up to 27 cancer-related functional prediction tasks, which involved multiple cancer cell growth processes and cancer hallmarks. Meanwhile, we have also found that (epi)genetic regulatory features, such as TFs and histone modifications, serve as strong predictors for revealing the function of lncRNAs. Overall, FunlncModel is a strong and stable prediction model for identifying functional lncRNAs in specific cellular contexts. FunlncModel is available as a web server at https://bio.liclab.net/FunlncModel/.
Clinical Course of Isolated Recurrent, Persistent Complex Perianal Fistulas Without Luminal Crohn’s Disease: A Multicenter Case Series of 24 Patients
Authors: Fiske Hannah W , Tse Chung Sang , Al-Bawardy Badr , Magavi Pooja , Konijeti Gauree Gupta , Mao Eric , Fine Sean , Parian Alyssa , Lazarev Mark , Shah Samir A
Published: November 2024

Background

Isolated complex perianal fistulas, without luminal evidence of inflammatory bowel disease in the gastrointestinal tract, pose diagnostic and treatment dilemmas for gastroenterologists and colorectal surgeons. For patients who develop recurrent complex fistulas, a presumptive diagnosis of Crohn’s disease may be made. It is unclear whether these cases of isolated perianal disease in the absence of luminal inflammation truly represent isolated severe cryptoglandular fistulas or rather an early presentation of Crohn’s disease. We aimed to investigate the clinical course and outcomes of patients with isolated complex perianal fistulas.

Methods

In this retrospective multicenter case series across 6 institutions in the United States, we report the clinical course of patients with isolated recurrent complex perianal fistulas, including their diagnostic evaluation, medical and surgical therapies, and clinical outcomes.

Results

All patients (n = 24) required incision and drainage of perirectal abscesses. The majority received setons (n = 19, 79%), more intensive surgical interventions (n = 15, 62.5%, including fistulotomy/sphincterotomy, advancement flap, and ligation of the intersphincteric fistula tract), antibiotics (n = 17, 71%), and biologic therapy (n = 16, 67%). Nine patients (37.5%) underwent a combined medical-surgical approach with biologics and intensive surgical intervention. Despite surgical and/or medical management, active symptomatic complex perianal fistulas persisted in 58% (n = 14) of patients at follow-up (median 5.5 years, interquartile range 2.5-10 years); symptom remission was achieved in 21% (n = 5), and fistula closure in 21% (n = 5).

Conclusions

These cases highlight a multidisciplinary and multimodal approach when treating isolated complex perianal fistulas and their propensity to persist despite the incorporation of advanced therapies.
Evaluation of temporomandibular joint disc displacement with MRI-based radiomics analysis
Authors: Duyan Yüksel Hazal , Orhan Kaan , Evlice Burcu , Kaya Ömer
Published: November 2024

Objectives

The purpose of this study was to propose a machine learning model and assess its ability to classify temporomandibular joint (TMJ) disc displacements on MR T1-weighted and proton density-weighted images.

Methods

This retrospective cohort study included 180 TMJs from 90 patients with TMJ signs and symptoms. A radiomics platform was used to extract imaging features of disc displacements. Thereafter, different machine learning algorithms and logistic regression were implemented on radiomics features for feature selection, classification, and prediction. The radiomics features included first-order statistics, size- and shape-based features, and texture features. Six classifiers, including logistic regression, random forest, decision tree, k-nearest neighbours (KNN), XGBoost, and support vector machine were used for a model building which could predict the TMJ disc displacements. The performance of models was evaluated by sensitivity, specificity, and ROC curve.

Results

KNN classifier was found to be the most optimal machine learning model for prediction of TMJ disc displacements. The AUC, sensitivity, and specificity for the training set were 0.944, 0.771, 0.918 for normal, anterior disc displacement with reduction (ADDwR) and anterior disc displacement without reduction (ADDwoR) while testing set were 0.913, 0.716, and 1 for normal, ADDwR, and ADDwoR. For TMJ disc displacements, skewness, root mean squared, kurtosis, minimum, large area low grey level emphasis, grey level non-uniformity, and long-run high grey level emphasis, were selected as optimal features.

Conclusions

This study has proposed a machine learning model by KNN analysis on TMJ MR images, which can be used for TMJ disc displacements.
Based proteomics analyses reveal response mechanisms of Apis mellifera (Hymenoptera: Apidae) against the heat stress
Authors: Li Xinyu
Published: November 2024

Heat stress can significantly affect the survival, metabolism, and reproduction of honeybees. It is important to understand the proteomic changes of honeybees under heat stress to understand the molecular mechanism behind heat resistance. However, the proteomic changes of honeybees under heat stress are poorly understood. We analyzed the proteomic changes of Apis mellifera Ligustica (Hymenoptera: Apidae) under heat stress using mass spectrometry-based proteomics with TMT (Tandem mass tags) stable isotope labeling. A total of 3,799 proteins were identified, 85 of which differentially abundance between experimental groups. The most significant categories affected by heat stress were associated with transcription and translation processes, metabolism, and stress-resistant pathways. We found that heat stress altered the protein profiles in A. mellifera, with momentous resist proteins being upregulated in heat groups. These results show a proof of molecular details that A. mellifera can respond to heat stress by increasing resist proteins. Our findings add research basis for studying the molecular mechanisms of honeybees’ resistance to heat stress. The differentially expressed proteins identified in this study can be used as biomarkers of heat stress in bees, and provide a foundation for future research on honeybees under heat stress. Our in-depth proteomic analysis provides new insights into how bees cope with heat stress.
Young and naïve B cells are a diagnostic pitfall in pediatric tonsillectomies
Authors: Tillotson Sophie , Shi Ping , Ray Elizabeth , Seifert Robert P
Published: November 2024

Tonsillar marginal zone hyperplasia may mimic mucosa-associated lymphoid tissue lymphoma, a rare diagnosis in children. Histologically, both entities can demonstrate expansion of the marginal zone with disruption of follicular architecture. However, marginal zone hyperplasia may appear polyclonal by flow cytometry. We present two pediatric tonsillectomy cases with tonsillar marginal zone hyperplasia and discuss the diagnostic challenges this poses in the pediatric population. Both tonsillectomies demonstrated expansion of marginal zones with partial architectural effacement, and flow cytometric analysis of both cases detected lambda light chain restricted, CD20(bright) B cells without CD38. Authors have suggested that the lambda restricted B cells in this setting represent naïve, unmutated B cells with preferential, but polyclonal, lambda expression. Our cases are in line with this thought. While robust, BIOMED-2 primer PCR can show dominant IgK peaks, which may be misinterpreted. This presents a diagnostic pitfall in the workup of pediatric tonsils that community pathologists must consider.
Multiwavelength investigations of PKS 2300–18: S-shaped radio quasar with precessing jets and double-peaked broad emission-line spectrum
Authors: Misra Arpita , Jamrozy Marek , Weżgowiec Marek , Kozieł-Wierzbowska Dorota
Published: November 2024

S-shaped radio galaxy jets are prime sources for investigating the dynamic interplay between the central active galactic nucleus (AGN), the jets, and the ambient intergalactic medium. These sources are excellent candidates for studying jet precession, as their S-shaped inversion symmetry strongly indicates underlying precession. We present a multiwavelength analysis of the giant inversion-symmetric S-shaped radio galaxy PKS 2300$-$18, which spans 0.76 Mpc. The host is a quasar at a redshift of 0.128, displaying disturbed optical morphology due to an ongoing merger with a companion galaxy. We conducted a broad-band radio spectral study using multifrequency data ranging from 183 MHz to 6 GHz, incorporating dedicated observations with the upgraded Giant Metrewave Radio Telescope (uGMRT) and Karl G. Jansky Very Large Array (JVLA) alongside archival radio data. A particle injection model was fitted to the spectra of different regions of the source to perform ageing analysis, which was supplemented with a kinematic jet precession model. The ageing analysis revealed a maximum plasma age of $\sim$ 40 Myr, while the jet precession model indicated a precession period of $\sim$ 12 Myr. ROentgen SATellite (ROSAT) data revealed an X-ray halo of Mpc size, and from Chandra the AGN X-ray spectrum was modelled using thermal and power-law components. The optical spectrum displaying double-peaked broad emission lines was modelled, indicating complex broad-line region kinematics at the centre with the possibility of a binary SMBH. We present the results of our multiwavelength analysis of the source, spanning scales from a few light-days to a few Mpc, and discuss its potential evolutionary path.
A natural variant of NON-RIPENING promotes fruit ripening in watermelon
Authors: Wang Jinfang , Yu Yongtao , Guo Shaogui , Zhang Jie , Ren Yi , Tian Shouwei , Li Maoying , Liao Shengjin , Gong Guoyi , Zhang Haiying , Xu Yong
Published: November 2024

The regulation of non-climacteric fruit ripening by the transcription factor NON-RIPENING (NOR) is poorly understood. Here, we identified that the NOR homolog in the non-climacteric fruit watermelon (Citrullus lanatus) was located within the selective sweep and sweetness quantitative trait locus that was selected during domestication from landraces to cultivars. ClNOR knockout substantially delayed fruit ripening, and the fruits of the knockout plants had lower abscisic acid (ABA) levels, lighter colored flesh, and were less sweet compared to wild type. Transcriptome analysis and DNA affinity purification sequencing revealed that ClNOR targeted the Basic Leucine Zipper gene ClbZIP1, which links ClNOR to genes that do not have a ClNOR-binding motif in their promoters, such as the ABA biosynthesis gene, 9-cis-epoxycarotenoid dioxygenase ClNCED1 and the chromoplast phosphate transporter gene ClPHT4;2. The double mutant Clnor Clbzip1 exhibited delayed fruit ripening, lower ABA level, and lighter colored flesh. Its delayed ripening phenotype was stronger than that of the Clbzip1 single mutant. Additionally, the ClNORT,T haplotype in cultivated watermelon resulted in higher ClbZIP1 expression, but ClNORC,T from landraces and ClNORC,G from ancestral watermelon did not. Heterologous ClNORT,T expression rescued the delayed ripening phenotype of the Slnor knockout in tomato (Solanum lycopersicum). This natural variant (564T/C) of ClNOR promoted fruit ripening by enhancing target genes transcription. Overall, these findings will help elucidate the evolutionary mechanisms of nonclimacteric fruit ripening.
Role of vitamin D3 in mitigating sodium arsenite-induced neurotoxicity in male rats
Authors: Abdou Heba Mohamed , Saad Alaa Mohamed , Abd Elkader Heba-Tallah Abd Elrahim , Essawy Amina E
Published: November 2024

Arsenic is associated with various neurological disorders, notably affecting memory and cognitive functions. The current study examined the protective effects of vitamin D3 (Vit. D3) in countering oxidative stress, neuroinflammation and apoptosis induced by sodium arsenite (SA) in the cerebral cortex of rats. Male Wistar rats were subjected to a daily oral administration of sodium arsenite (NaAsO2, SA) at a dosage of 5 mg/kg, along with 500 IU/kg of Vit. D3, and a combination of both substances for four weeks. The results indicated that Vit. D3 effectively mitigated the SA-induced increase in oxidative stress markers, thiobarbituric acid reactive substances (TBARS) and nitric oxide (NO), the decrease in antioxidants (reduced glutathione; GSH, superoxide dismutase; SOD, catalase; CAT, and glutathione peroxidase; GPx), as well as the increase in pro-inflammatory markers including, tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), and amyloid-beta (Aβ)1–42. Furthermore, Vit. D3 reversed the alterations in the neurochemicals acetylcholinesterase (AchE), monoamine oxidase (MAO), dopamine (DA), and acetylcholine (Ach) and ameliorated the histopathological changes in the cerebral cortex. Moreover, immunohistochemical analyses revealed that Vit. D3 reduced the SA-induced overexpression of cerebral cysteine aspartate-specific protease-3 (caspase-3) and glial fibrillary acidic protein (GFAP) in the cerebral cortex of male rats. Consequently, the co-administration of Vit. D3 can protect the cerebral cortex against SA-induced neurotoxicity, primarily through its antioxidant, anti-inflammatory, anti-apoptotic, and anti-astrogliosis effects.
Lower Incidence of ASP Requiring Surgery With Minimally Invasive TLIF Than With Open PLIF
Authors: Roh Young-Ho , Soh Jaewan , Lee Jae Chul , Jang Hae-Dong , Choi Sung-Woo , Shin Byung-Joon
Published: November 2024

Study Design:

Retrospective analysis.

Objective:

To assess the incidence of and risk factors for adjacent segment pathology (ASP) requiring surgery among patients previously treated with spinal fusion. Survival of the adjacent segment was compared in patients undergoing open posterior lumbar interbody fusion (O-PLIF) versus minimally invasive transforaminal interbody fusion (MI-TLIF).

Summary of Background Data:

Compared with O-PLIF, MI-TLIF may reduce ASP in the long term by preserving more of the paraspinal muscle and ligamentous structures connected to adjacent segments.

Methods:

The study population consisted of 740 consecutive patients who had undergone lumbar spinal fusion of 3 or fewer segments. O-PLIF was performed in 564 patients, and MI-TLIF in 176 patients. The incidence and prevalence of revision surgery for ASP were calculated using the Kaplan-Meier method. A risk factor analysis was performed using the log-rank test and a Cox regression analysis.

Results:

After index spinal fusion, 26 patients (3.5%) underwent additional surgery for ASP. Kaplan-Meier analysis predicted a disease-free survival rate of adjacent segments in 87.2% at 10 years after the index operation. The incidence of ASP requiring surgery within 10 years was 16.4% after O-PLIF and 6.1% after MI-TLIF (P=0.045). This result was supported by the Cox regression analysis, which showed a significant difference between MI-TLIF and O-PLIF (P=0.034). The hazard ratio of revision surgery was about 3 times higher with O-PLIF than with MI-TLIF. Patients 65 years or older at the time of the index operation were 2.9 times more likely to undergo revision surgery than those younger than 65 years (P=0.015).

Conclusions:

MI-TLIF results in less ASP requiring surgery than O-PLIF. 65 years or older is an independent risk factor for ASP. By preserving the soft tissues, MI-TLIF may result in a lower incidence of ASP than the open technique.

Level of Evidence:

Level 3.
Prognostic impact of elevated C-reactive protein and procalcitonin in patients with extensive-stage small cell lung cancer
Authors: Buğday İrfan , İnanç Mevlüde , Özkan Metin , Bozkurt Oktay , Coşar Ramazan , Firat Sedat Tarik , Mutlu Emel , Eser Murat , Dişli Ahmet Kürşad , Cengiz Muhammet
Published: November 2024

Small cell lung cancer (SCLC) constitutes around 15% of lung cancer cases and stands as the primary cause of cancer-related fatalities in men and the second leading cause in women globally. In this study, our objective was to evaluate the levels of C-reactive protein (CRP) and procalcitonin (PCT) in newly diagnosed extensive-stage SCLC patients without evidence of infection. We aimed to demonstrate that elevated CRP and PCT levels may not solely indicate infection but could also be elevated in malignancies. Furthermore, we sought to correlate these marker levels with patient and disease characteristics to elucidate the relationship between these inflammation markers and disease progression. A total of 115 patients who were pathologically and radiologically diagnosed with extensive-stage SCLC between January 2020 and December 2022 and who had received no prior treatment were included in the study. The Kaplan–Meier analysis revealed a median progression-free survival (PFS) of 7.46 months [95% confidence interval (CI), 6.85–8.07] and a median overall survival (OS) of 10.50 months (95% CI, 8.69–12.30) for all patients. In the group with elevated PCT, the median PFS was 6.73 months (95% CI, 3.92–9.54), whereas it was 7.86 months (95% CI, 7.13–8.59) in the group with normal PCT (P = 0.002). Similarly, the median OS was 9.10 months (95% CI, 5.61–12.58) in the elevated PCT group and 11.66 months (95% CI, 9.59–13.74) in the normal PCT group (P = 0.006). Patients with elevated procalcitonin (PRC) levels at the time of diagnosis exhibited shorter PFS and OS durations compared to patients with normal PRC levels. Furthermore, elevated CRP has also been demonstrated to correlate with poorer prognosis in extensive-stage SCLC.
Meta-Analysis on the Racial Disparity of Outcomes Following Alcohol Septal Ablation in Hypertrophic Cardiomyopathy
Authors: Jain Hritvik , Tariq Muhammad Daoud , Hurjkaliani Sonia , Ahmed Mushood , Ahmed Raheel , Jain Jyoti , Odat Ramez M. , Ullah Irfan , Khan Rozi
Published: November 2024

Hypertrophic cardiomyopathy (HCM) is a prevalent cardiac condition that often leads to heart failure, exertional syncope, and sudden cardiac death. Despite the availability of various treatments for HCM, such as septal reduction therapy through surgical septal myectomy or alcohol septal ablation (ASA), disparities in access to care and treatment outcomes persist, particularly among marginalized racial and ethnic groups. These disparities underscore the importance of understanding the influence of race, ethnicity, and regional factors on the management and outcomes of HCM, necessitating a closer examination of whether access to ASA and its associated benefits is equitably distributed across diverse populations. A comprehensive literature search was conducted on various electronic databases aimed to identify studies evaluating the odds of undergoing ASA in HCM in racial subgroups and outcomes like all-cause mortality and stroke. Three studies were included in this meta-analysis with a total sample size of 24,939 HCM patients. Adjusted odds ratio (OR) or pooled risk ratios (RR) with 95% confidence intervals (CI) were calculated using a random-effects model. Blacks were significantly less likely to undergo ASA for HCM (OR, 0.64; 95% CI, 0.57–0.72; P < 0.01) as compared to white patients; however, no differences in all-cause mortality (RR, 0.97; 95% CI, 0.54–1.75) and stroke (RR, 1.29; 95% CI, 0.76–2.18) were noted. In conclusion, this meta-analysis highlights a significant association between race and the likelihood of undergoing ASA among patients with HCM, with minority racial groups potentially facing barriers to accessing this advanced treatment.
FOUR-YEAR OUTCOMES AFTER INTRAVITREAL AFLIBERCEPT FOR MACULAR NEOVASCULARIZATION IN PATIENTS WITH PATHOLOGIC MYOPIA
Authors: Mizuno-Onishi Yuka , Igarashi Tae , Uramoto Kengo , Kaneko Yuichiro , Nagaoka Natsuko , Yoshida Takeshi , Ohno-Matsui Kyoko
Published: November 2024

Purpose:

The natural course of the visual acuity in eyes with myopic macular neovascularization is poor. Intravitreal injections of anti-vascular endothelial growth factor agents have demonstrated safety and efficacy in the short term for managing myopic macular neovascularization. The purpose of this study was to determine the 4-year outcomes of intravitreal aflibercept injections.

Methods:

A retrospective monocentric study including 49 eyes of 48 patients diagnosed with myopic macular neovascularization. These patients underwent treatment with intravitreal aflibercept using the pro re nata regimen after the first injection. The minimum follow-up duration was 4 years.

Results:

The patients had an average age of 63.8 years and an average axial length of 29.7 mm. The mean number of intravitreal aflibercept injections was 1.6, and 30 eyes (61.2%) had a single injection. At the baseline and at 1, 2, 3, and 4 years, the mean best-corrected visual acuities were 20/45, 20/41, 20/43, 20/51, and 20/53, respectively. The differences in the best-corrected visual acuity at the different times from that at the baseline were not significant.

Conclusion:

Intravitreal aflibercept therapy with the pro re nata regimen provides a 4-year visual benefit in eyes with myopic macular neovascularization, and it is better than the reported natural course in maintaining the best-corrected visual acuity.
Comparison of Cochet–Bonnet, Dental Floss, and Cotton Wisp With Applications to Corneal Sensation Testing
Authors: Schultheis William Grant , Hampton Thomas , Gensheimer William
Published: November 2024

Purpose:

The measurement of corneal sensation can be useful in the diagnosis of corneal neuropathies. Although the Cochet–Bonnet esthesiometer (CB) is the gold standard, cotton wisp (CW) and dental floss are commonly used in clinical practice.

Methods:

We assessed the steady-state force of thick dental floss (tkDF), thin dental floss (tnDF), and CW compared with that of CB. We surveyed cornea/refractive specialists (CRS) and noncornea/refractive specialists (NCRS) for frequency and method by which corneal sensation was checked.

Results:

Compared with CB, the maximum force applied by tkDF was 0.92 grams more (P << 0.05), 0.15 grams more for tnDF (P < 0.05), and 0.23 grams less for CW (P < 0.05). Compared with CB, force per unit length was 0.13 g/mm higher for tkDF (P << 0.05), 0.001 g/mm higher for tnDF (P = 0.44), and 0.008 g/mm lower for CW (P = 0.10). We collected responses from 182/284 CRS and 102/284 NCRS. 12/182 CRS checked cornea sensation 0x/month compared with 42/102 NCRS. A total of 103/182 CRS and 54/102 NCRS checked cornea sensation 1-5x/month. CW was the most common tool used for CRS (115/170) and NCRS (53/60).

Conclusions:

tnDF provides the best analog for the CB. CW provides a small amount of force over a large range of lengths and may be a useful screening tool. tkDF is less suitable for screening. CRS check corneal sensation at a higher rate than NCRS. CW was the most common method used in both groups.
The effect of cataract surgery on lowering intraocular pressure
Authors: Shah Yesha S. , Garg Anupam K. , Ramulu Pradeep Y.
Published: November 2024

Purpose of review

To review the literature evaluating the effectiveness of cataract surgery alone and cataract surgery in combination with other procedures and surgeries on intraocular pressure (IOP) in patients with ocular hypertension and glaucoma.

Recent findings

Recent studies of large trials have shown the IOP-lowering effect of cataract surgery and the beneficial effect of minimally invasive glaucoma surgery (MIGS). More studies are being published on when to use cataract surgery alone, with MIGS, or with traditional glaucoma surgeries for both primary open angle glaucoma and primary angle closure glaucoma.

Patients with ocular hypertension and visually significant cataracts would benefit from cataract surgery alone to lower intraocular pressure. Patients with mild to moderate glaucoma would likely benefit from cataract surgery and MIGS to achieve a lower IOP. Patients with more advanced glaucoma would benefit from cataract surgery combined with a traditional incisional glaucoma surgery. Clear lens extraction can be used in patients with primary angle closure and early primary angle closure glaucoma. In patients with more advanced disease, phacoemulsification and another glaucoma surgery is likely to be required to achieve IOP control. MIGS are starting to be used in angle closure glaucoma, although more research needs to be done to define its role.