Multiple Series Research Articles

Abstract 6537: A novel CCR4 antagonist induces potent anti-tumor response through inhibition of Treg migration into the tumor microenvironment

Abstract Regulatory T cells (Tregs), an immunosuppressive subset of CD4+ T cells, play a vital role in maintaining immune homeostasis by regulating response to self antigens and maintaining tolerance. On the contrary, Tregs infiltrating the tumor microenvironment (TME) impede effective anti-tumor immunity by inhibiting tumor-specific T cell responses and generating a suppressive TME, thus promoting tumor progression. Clinically, Tregs have been proven to play a significant role in resistance to immune checkpoint inhibitors (ICIs) leading to lower response rates. Hence, targeting Tregs would lead to activation of tumor-specific effector T cells and improved long-term anti-tumor immune responses with ICI treatment. CCR4, a chemokine receptor highly expressed on Tregs, spearhead the migration of Tregs and their accumulation in the TME, by responding to the chemokines CCL22 and CCL17 secreted by the inflamed cells in the tumor. CCR4 expression is associated with poor prognosis in various solid tumors. This warrants the therapeutic targeting of CCR4-expressing Tregs to enable effective and durable anti-tumor immune responses. We sought to discover and develop novel small molecule antagonists of CCR4 for use in cancer therapy. Multiple series of CCR4 antagonists were identified by iterative medicinal chemistry efforts and SAR based approach. These compounds were optimized towards attaining required potency, acceptable physicochemical properties, high selectivity and desirable pharmacokinetic profile to achieve anti-tumor activity. Aurigene’s CCR4 antagonists exhibited potent inhibition of CCR4 activity in the reporter-based β-arrestin recruitment assay. This translated well into potent inhibition of CCL22-mediated chemotaxis of CCR4-expressing Tregs in an in vitro cell migration assay. Furthemore, the lead compounds showed desirable drug-like properties and excellent pharmacokinetic exposure in rodents. In an ongoing study in a syngeneic mice tumor model, one of the lead compounds is being evaluated for impact on Treg infiltration, CD8:Treg ratio in the tumor and efficacy. In summary, we have identified novel CCR4 antagonists with desirable drug-like properties that are being evaluated further to identify a clinical candidate. Citation Format: Rashmi Nair, Chandrasekhar Abbineni, Krishna Chaitanya Talluri, Amit A Dhudashiya, Aravind AB, NaveenR Kumar, Ramya R, D Balasubramanyam, Pathur Obanna, Rabin Madhaiyan, DS Samiulla, Girish Daginakatte, Kishore Narayanan, Kavitha Nellore, Shekar Chelur, Susanta Samajdar, Murali Ramachandra. A novel CCR4 antagonist induces potent anti-tumor response through inhibition of Treg migration into the tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6537.

Geochemical proxies for deep-sea temperature and nutrient content in cold-water bamboo corals

The impact of warming, acidification, and deoxygenation on deep-sea environments is a growing concern. Historical records are sparse, particularly at high latitudes, making climate change projections challenging. Indirect proxies, such as trace element composition of marine carbonates, such as coral skeletons, can offer an alternative method to fill data gaps but have not been realised. Here, using Laser Ablation Triple-Quadrupole Inductively Coupled Plasma Mass Spectrometry (LA-QQQ-ICP-MS), we examined micrometre-scale element variation within and between individual colonies of the bamboo coral Keratoisis sp. obtained from the Eastern Canadian Arctic. These data are used to assess the influence of biological variability on geochemical tracers for reconstructing past environmental conditions (temperature: Mg/Ca, Li/Mg, Sr/Ca, Ba/Ca, U/Ca; [Ba]SW: Ba/Ca). We place these data into context, based on a survey of literature data, using refined calibrations for high-Mg calcitic Octocorals. We find reproducible (2σ relative coefficient of variation) values of Mg/Ca (3%) and Ba/Ca (6%) along the radial growth axis of all colonies and internodes of Keratoisis sp., indicating that these signals are likely suitable for environmental reconstructions. After revising the available multi-taxa calibrations for Mg/Ca (0.316 ± 0.026 °C/mmol/mol, R2 = 0.87, p < 0.001) and Ba/Ca ([Ba/Ca μmol/mol] = 0.148 ± 0.005 [BaSW nmol/kg], R2 = 0.97, p < 0.001), we show that vital effects within and among Keratoisis sp. colonies strongly influence reconstructed temperature and [Ba]SW, but this can be somewhat mitigated by combining multiple internode transects from one colony into a single composite series. Despite the ontogenetic variability, all colonies reveal a gradual deep-water cooling trend since the early 21st century and synchronised, multi-year spikes in Ba/Ca (and hence [Ba]SW) that suggest substantial and coherent barium inputs to the seafloor. Our study confirms the reliability of Mg/Ca and Ba/Ca proxies in high-Mg bamboo corals for detecting multi-annual temperature and seawater barium variations in cold-water environments, but further investigation into micro-scale element behaviour influenced by biotic processes in these corals is needed to enhance confidence in reconstructions at finer spatial and temporal resolutions. We conclude that employing empirical calibrations based on multi-taxa approaches can increase the certainty of capturing regional changes in the environment more accurately than a single species calibration, while leveraging multiple element series to account for biological-induced variability improves single colony reconstructions.

Potent small molecule inhibitors against the 3C protease of foot-and-mouth disease virus.

Foot-and-mouth disease (FMD) is one of the most devastating diseases of livestock which can cause significant economic losses, especially when introduced to FMD-free countries. FMD virus (FMDV) belongs to the family Picornaviridae and is antigenically heterogeneous with seven established serotypes. The prevailing preventive and control strategies are limited to restriction of animal movement and elimination of infected or exposed animals, which can be potentially combined with vaccination. However, FMD vaccination has limitations including delayed protection and lack of cross-protection against different serotypes. Recently, antiviral drug use for FMD outbreaks has increasingly been recognized as a potential tool to augment the existing early response strategies, but limited research has been reported on potential antiviral compounds for FMDV. FMDV 3C protease (3Cpro) cleaves the viral-encoded polyprotein into mature and functional proteins during viral replication. The essential role of viral 3Cpro in viral replication and the high conservation of 3Cpro among different FMDV serotypes make it an excellent target for antiviral drug development. We have previously reported multiple series of inhibitors against picornavirus 3Cpro or 3C-like proteases (3CLpros) encoded by coronaviruses or caliciviruses. In this study, we conducted structure-activity relationship studies for our in-house focused compound library containing 3Cpro or 3CLpro inhibitors against FMDV 3Cpro using enzyme and cell-based assays. Herein, we report the discovery of aldehyde and α-ketoamide inhibitors of FMDV 3Cpro with high potency. These data inform future preclinical studies that are related to the advancement of these compounds further along the drug development pathway.IMPORTANCEFood-and-mouth disease (FMD) virus (FMDV) causes devastating disease in cloven-hoofed animals with a significant economic impact. Emergency response to FMD outbreaks to limit FMD spread is critical, and the use of antivirals may overcome the limitations of existing control measures by providing immediate protection for susceptible animals. FMDV encodes 3C protease (3Cpro), which is essential for virus replication and an attractive target for antiviral drug discovery. Here, we report a structure-activity relationship study on multiple series of protease inhibitors and identified potent inhibitors of FMDV 3Cpro. Our results suggest that these compounds have the potential for further development as FMD antivirals.

The ratios conjecture for real Dirichlet characters and multiple Dirichlet series

Conrey, Farmer and Zirnbauer introduced a recipe to find asymptotic formulas for the sum of ratios of products of shifted L-functions. These ratios conjectures are very powerful and can be used to determine many statistics of L-functions, including moments or statistics about the distribution of zeros. We consider the family of real Dirichlet characters, and use multiple Dirichlet series to prove the ratios conjectures with one shift in the numerator and denominator in some range of the shifts. This range can be improved by extending the family to include non-primitive characters. All of the results are conditional under the Generalized Riemann hypothesis. This extended range is good enough to enable us to compute an asymptotic formula for the sum of shifted logarithmic derivatives near the critical line. As an application, we compute the one-level density for test functions whose Fourier transform is supported in ( − 2 , 2 ) \left (-2,2\right ) , including lower-order terms.

Evolutionary analysis of rainstorm momentum and non-stationary variating patterns in response to climatic changes across diverse terrains

This study aims to analyze time-series measurements encompassing rainstorm events with over a century of datasets to identify rainstorm evolution and dimensional transitions in non-stationarity. Rainstorm events are identified using partial duration series (PDS) to extract changes in rainstorm characteristics, namely maximum intensity (MAXI), duration (D), total rainfall (TR), and average rainfall intensity (ARI), in response to climate change. Ensemble empirical mode decomposition is used for trend filtering and non-stationary identification to explore spatiotemporal insight patterns. Trend models for the first–second-order moments of rainstorm characteristics are used to formulate the identified mean–variance trends using combined multi-dimensional linear-parabolic regression. Best-fitting combinations of various distributions (probability density functions) and trend models for multiple characteristic series are identified based on the Akaike information criterion. We analyze the dimensional transition in rainfall non-stationarity based on sensitivity analysis using PDS to determine its natural geophysical causes. The integrated methodology was applied to the data retrieved from nine weather stations in Taiwan. Our findings reveal rainstorm characteristics of “short D but high rainfall intensity” or “lower MAXI but high TR” across multiple stations. The parabolic trend of the first-order moment (i.e., mean) of ARI, D, and TR appears at the endpoint of the mountain ranges. Areas receiving monsoons and those on the windward plain show a rising parabolic trend in the first- and second-order moments (i.e., mean–variance) characterizing MAXI, implying that the occurrence frequency and magnitude of extreme MAXI increases. Non-stationary transitions in MAXI appear for mountain ranges exposed to the monsoon co-movement effect on both windward and leeward sides. Stations in the plains and rift valleys show upgraded and downgraded transitions in the non-stationary dimensions for D, respectively.

Expanded Brain CT Dataset for the Development of AI Systems for Intracranial Hemorrhage Detection and Classification

Intracranial hemorrhage (ICH) is a dangerous life-threatening condition leading to disability. Timely and high-quality diagnosis plays a huge role in the course and outcome of this disease. The gold standard in determining ICH is computed tomography. This method requires a prompt involvement of highly qualified personnel, which is not always possible, for example, in case of a staff shortage or increased workload. In such a situation, every minute counts, and time can be lost. The solution to this problem seems to be a set of diagnostic decisions, including the use of artificial intelligence, which will help to identify patients with ICH in a timely manner and provide prompt and quality medical care. However, the main obstacle to the development of artificial intelligence is a lack of high-quality datasets for training and testing. In this paper, we present a dataset including 800 brain CT scans consisting of multiple series of DICOM images with and without signs of ICH, enriched with clinical and technical parameters, as well as the methodology of its generation utilizing natural language processing tools. The dataset is publicly available, which contributes to increased competition in the development of artificial intelligence systems and their advancement and quality improvement.

Counterface soil type and loading condition effects on granular/cohesive soil – Geofoam interface shear behavior

Soil – geofoam interfaces have been studied through an extensive experimental program by performing multiple series of interface shear tests using two different granular soils (i.e. beach sand and construction material sand) and one cohesive soil (i.e. bentonite clay) as well as a soil mixture containing 75% sand and 25% clay by dry weight at distinct loading conditions (i.e. normal stresses (σ): 25, 100, 250; low, moderate, high loading conditions, respectively). Using the shear stress versus horizontal displacement curves obtained, some important engineering design parameters including peak shear stress, residual shear stress, interface sensitivity (i.e., peak/residual ratio) and displacement required to reach peak stress have been determined and the variations in those interface mechanical properties as a function of loading condition and counterface soil type have been investigated. It was shown that the peak as well as residual shear stresses increased with an increase in normal stress for all the interface systems tested. Further, the granular soil (sand) interfaces demonstrated relatively larger frictional strengths (both peak and residual) as compared to both the cohesive soil (clay) interface and the sand/clay admixture soil interface. Additionally, the higher the angularity of granular soil particles became, the larger the interface shear strengths (peak and residual), when sheared against geofoams, developed in light of experimental results attained as a result of interface shear tests on different material combinations. For comparison, the detected peak strength at average for the construction material sand, the beach sand, and the sand/clay admixture soil interfaces as compared to the bentonite clay interface were improved 59.8%, 43.4%, and 20.3%, respectively. Additionally, the detected residual strength at average for the construction material sand, the beach sand, and the sand/clay admixture soil interfaces as compared to the bentonite clay interface were improved 53.9%, 28.6%, and 15.4%, respectively.

Balanced multiple q-zeta values

We introduce the balanced multiple q-zeta values. They give a new model for multiple q-zeta values, whose product formula combines the shuffle and stuffle product for multiple zeta values in a natural way. Moreover, the balanced multiple q-zeta values are invariant under a very explicit involution. Thus, all relations among the balanced multiple q-zeta values are conjecturally of a very simple shape. Examples of the balanced multiple q-zeta values are the classical Eisenstein series, and they also contain the combinatorial multiple Eisenstein series introduced in [3]. The construction of the balanced multiple q-zeta values is done on the level of generating series. We introduce a general setup relating Hoffman's quasi-shuffle products to explicit symmetries among generating series of words, which gives a clarifying approach to Ecalle's theory of bimoulds. This allows us to obtain an isomorphism between the underlying Hopf algebras of words related to the combinatorial bi-multiple Eisenstein series and the balanced multiple q-zeta values.

Multiple Kernel Synthesis of Head CT Using a Task-Based Loss Function

In CT imaging of the head, multiple image series are routinely reconstructed with different kernels and slice thicknesses. Reviewing the redundant information is an inefficient process for radiologists. We address this issue with a convolutional neural network (CNN)-based technique, synthesiZed Improved Resolution and Concurrent nOise reductioN (ZIRCON), that creates a single, thin, low-noise series that combines the favorable features from smooth and sharp head kernels. ZIRCON uses a CNN model with an autoencoder U-Net architecture that accepts two input channels (smooth- and sharp-kernel CT images) and combines their salient features to produce a single CT image. Image quality requirements are built into a task-based loss function with a smooth and sharp loss terms specific to anatomical regions. The model is trained using supervised learning with paired routine-dose clinical non-contrast head CT images as training targets and simulated low-dose (25%) images as training inputs. One hundred unique de-identified clinical exams were used for training, ten for validation, and ten for testing. Visual comparisons and contrast measurements of ZIRCON revealed that thinner slices and the smooth-kernel loss function improved gray-white matter contrast. Combined with lower noise, this increased visibility of small soft-tissue features that would be otherwise impaired by partial volume averaging or noise. Line profile analysis showed that ZIRCON images largely retained sharpness compared to the sharp-kernel input images. ZIRCON combined desirable image quality properties of both smooth and sharp input kernels into a single, thin, low-noise series suitable for both brain and skull imaging.

Research on Correlation Analysis for Multidimensional Time Series Based on the Evolution Synchronization of Network Topology

We apply the inherent dynamic consistency of a dynamic system as the basis for correlation analysis among different variables in a system. We use network analysis to measure the correlativity of multiple variables, find the interdependence between multiple variables with nonlinear interactions, and study the complex relationship between the stock index and trading volume. We explore the change pattern of the number of edges in the networks derived from the correlation among different time series by gradually increasing the length of the time series. We found that the evolution trend of the corresponding network edges is the same or similar for multiple series with the same dynamic properties or mutual effects, which is called network topology evolution synchronization (NTES). The correlation among time series can be determined by investigating the existence of NTES. Using this method, we detected that both the stock price and trading volume are chaotic series and have complex correlations with varying randomness caused by different markets and series lengths.

Generalized Localization and Summability Almost Everywhere of Multiple Fourier Series and Integrals

Generalized Localization and Summability Almost Everywhere of Multiple Fourier Series and Integrals

Simulations of electric multiple unit series 413/417 drives on the electrified tracks of "Serbian Railways"

In the paper, the Matlab-Simulink model of simulation of operation of the ŽS 413/417 series electric multiple unit (EMU) in traction and braking mode is exposed where changes are observed: stator currents of three-phase traction motors, traction electric motor speeds and electric multiple unit, electromagnetic torque on the rotor shaft of the traction electric motor and DC bus voltage. The model allowed review of the listed parameters for: different allowed values of contact network voltage and total voltage distortion at the place of connection of the electric multiple unit to the contact network, different mechanical loads of electric multiple unit and traction electric motor and different train speeds and rotation of traction electric motors. Appropriate conclusions were made through the analysis of the simulation results obtained.

Vehicle Parameter and Electric Powertrain Efficiency Analysis Using Real-Driving Data

With the conversion from Internal Combustion Engine Vehicles (ICEV) to Battery Electric Vehicles (BEV) mainly promoted by CO2 emission targets, innovative powertrain concepts arose in the automotive industry. Original Equipment Manufacturers (OEMs) practice the socalled benchmarking to identify technological potentials in their competitor’s concepts and reduce their development costs by focusing on the best-performing technologies in the electric vehicle market. In contrast, these analyses mean significant expenses in terms of time and cost. Especially on vehicle level, preparing the vehicles for dynamometer tests and performing multiple test series on these test benches require high personnel and time capacities. In this work, we present a methodology that reduces the effort of benchmarking analyses on vehicle level by substituting dynamometer tests. This methodology describes the identification of vehicle parameters and the analysis of the electric powertrain’s efficiency. With no manipulation of the vehicle’s structure and low-cost test equipment, data is recorded on public roads during real-driving scenarios, demonstrating our procedure's simplicity and universal application. With the obtained vehicle parameters (i.e. Road Load Coefficients (RLCs), rolling and air resistance) and the electric powertrain’s efficiency map, we enable the parametrization of simulation models for further analyses. We validate our methodology based on tests performed on closed test tracks and a vehicle dynamometer.

Coefficients of multiple Fourier-Haar series and variational modulus of continuity

In this paper, we introduce the concept of a variational modulus of continuity for functions of several variables, give an estimate for the sum of the coefficients of a multiple Fourier-Haar series in terms of the variational modulus of continuity, and prove theorems of absolute convergence of series composed of the coefficients of multiple Fourier-Haar series. In this paper, we study the issue of the absolute convergence for multiple series composed of the Fourier-Haar coefficients of functions of several variables of bounded p-variation. We estimate the coefficients of a multiple Fourier-Haar series in terms of the variational modulus of continuity and prove the sufficiency theorem for the condition for the absolute convergence of series composed of the Fourier-Haar coefficients of the considered function class. This paper researches the question: under what conditions, imposed on the variational modulus of continuity of the fractional order of several variables functions, there is the absolute convergence for series composed of the coefficients of multiple Fourier-Haar series.

Pseudostarlikeness and Pseudoconvexity of Multiple Dirichlet Series

Let $p\in {\Bbb N}$, $s=(s_1,\ldots,s_p)\in {\Bbb C}^p$, $h=(h_1,\ldots,h_p)\in {\Bbb R}^p_+$, $(n)=(n_1,\ldots,n_p)\in {\Bbb N}^p$ and the sequences $\lambda_{(n)}=(\lambda^{(1)}_{n_1},\ldots,\lambda^{(p)}_{n_p})$ are such that $0&amp;lt;\lambda^{(j)}_1&amp;lt;\lambda^{(j)}_k&amp;lt;\lambda^{(j)}_{k+1}\uparrow+\infty$ as $k\to\infty$ for every $j=1,\ldots,p$. For $a=(a_1,\ldots,a_p)$ and $c=(c_1,\ldots,c_p)$ let $(a,c)=a_1c_1+\ldots+a_pc_p$, and we say that $a&amp;gt;c$ if $a_j&amp;gt; c_j$ for all $1\le j\le p$. For a multiple Dirichlet series \begin{align*}F(s)=e^{(s,h)}+\sum\limits_{\lambda_{(n)}&amp;gt;h}f_{(n)}\exp\{(\lambda_{(n)},s)\}\end{align*} absolutely converges in $\Pi^p_0=\{s:\text{Re}\,s&amp;lt;0\}$, concepts of pseudostarlikeness and pseudoconvexity are introduced and criteria for pseudostarlikeness and the pseudoconvexity are proved. Using the obtained results, we investigated neighborhoods of multiple Dirichlet series, Hadamard compositions, and properties of solutions of some differential equations.

Twnbiome: a public database of the healthy Taiwanese gut microbiome

With new advances in next generation sequencing (NGS) technology at reduced costs, research on bacterial genomes in the environment has become affordable. Compared to traditional methods, NGS provides high-throughput sequencing reads and the ability to identify many species in the microbiome that were previously unknown. Numerous bioinformatics tools and algorithms have been developed to conduct such analyses. However, in order to obtain biologically meaningful results, the researcher must select the proper tools and combine them to construct an efficient pipeline. This complex procedure may include tens of tools, each of which require correct parameter settings. Furthermore, an NGS data analysis involves multiple series of command-line tools and requires extensive computational resources, which imposes a high barrier for biologists and clinicians to conduct NGS analysis and even interpret their own data. Therefore, we established a public gut microbiome database, which we call Twnbiome, created using healthy subjects from Taiwan, with the goal of enabling microbiota research for the Taiwanese population. Twnbiome provides users with a baseline gut microbiome panel from a healthy Taiwanese cohort, which can be utilized as a reference for conducting case-control studies for a variety of diseases. It is an interactive, informative, and user-friendly database. Twnbiome additionally offers an analysis pipeline, where users can upload their data and download analyzed results. Twnbiome offers an online database which non-bioinformatics users such as clinicians and doctors can not only utilize to access a control set of data, but also analyze raw data with a few easy clicks. All results are customizable with ready-made plots and easily downloadable tables. Database URL: http://twnbiome.cgm.ntu.edu.tw/.

Evaluation of image quality and radiation dose in computed tomography urography following tube voltage optimisation

IntroductionComputed tomography urography (CTU) comprehensively evaluates the urinary tract. However, the procedure is associated with a high radiation dose due to multiple scan series and therefore requires optimisation. The study performed CTU protocol optimisation based on a reduction in tube voltage (kV) using quality assurance (QA) phantom and clinical images and evaluated image quality and radiation dose. MethodsThe study was prospectively conducted on patients referred for CTU. The patients were grouped into A and B and were scanned with the standard protocol, a protocol used for the routine CTU at the CT centre before optimisation, and optimised protocol, a protocol with reduced kV respectively. The protocols were first tried on a quality assurance (QA) phantom before being applied to patients, and image quality was assessed based on signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). In addition, the clinical images were assessed based on the visibility of the anatomical criteria for CT images by five observers with >5 years of experience. The data were analysed using both visual grading characteristic (VGC) curves and statistical package for social sciences (SPSS) version 22.0. ResultsThe dose was significantly lower in the optimised protocol with a 10 % reduction in both volume computed tomography dose index and (CTDIvol) and dose length product (DLP) for the phantom images, and a 26 % reduction in CTDIvol and 28 % in DLP for the clinical images. However, there was no significant difference in image quality noted between the standard and optimised protocols based on the quantitative and qualitative image quality evaluation using both the QA phantom and clinical images. ConclusionThe findings revealed a significant dose reduction in the optimised protocol. Further, image quality in standard and optimised protocols did not differ significantly based on quantitative and qualitative methods. Implication for practicekV optimisation in contrast-enhanced procedures provides dose reduction and should be encouraged in the medical imaging departments.

On the generalized β-absolute convergence of single and multiple Fourier series

In this paper, we provide sufficient conditions for the generalized β-absolute convergence of multiple Fourier series of a function of p-(Λ1, ... ,ΛN)-bounded variation.

On Pringsheim Convergence of a Subsequence of Partial Sums of a Multiple Trigonometric Fourier Series

On Pringsheim Convergence of a Subsequence of Partial Sums of a Multiple Trigonometric Fourier Series

Malignant Transformation of Long-Standing Ileal Crohn's Disease Likely Favors Signet Ring Cell Adenocarcinoma Histology.

Signet ring cell adenocarcinomas (SRCCs) are a rare and aggressive histological subtype of adenocarcinomas typically with poor prognosis usually secondary to late stage at detection. In the small bowel, they constitute only 1% of all malignancies. In the last decade, there have been multiple case reports and small case series that have identified SRCCs, typically in the ileum, in patients with Crohn's disease. Crohn's disease is a transmural inflammatory condition that normally manifests in the distal ileum and colon, and is known to temporally increase the risk of malignancy. Given the profound rarity of SRCCs, establishing an association between Crohn's disease and SRCC is challenging. In this study, we performed a systematic review of case reports and small case series describing small bowel SRCCs in Crohn's disease patients. Most cases were found in the distal/terminal ileum, at a mean age of 59 years old. Virtually all tumors were locally advanced (pathological T stage 3 and 4), typically with at least N1 nodal disease. Two case studies (one is a case-control study and the other a cohort design) demonstrated that small bowel SRCC, as opposed to conventional adenocarcinoma, was significantly correlated to a history of Crohn's disease (35% vs. 0%, 73.5% vs. 28.5%), with a propensity to arise in the ileum (95% vs. 30%, 66.7% vs. 42.1%), and at earlier mean age (43 vs. 68 years, 53.7 vs. 61.7 years). We additionally used the Surveillance, Epidemiology, and End Results (SEER) database for insights into the clinicoepidemiological characteristics of ileum SRCCs. SRCCs composed 28.1% of all ileal SRCCs, compared to 11.0% for the adenocarcinomas, with a younger age at diagnosis (60.7 vs. 64.6 years), more distant disease at presentation (41.3% vs. 26.4%), and shorter overall median survival time (20 vs. 39 months). In summary, while there is limited direct evidence to support an association between small bowel SRCC and Crohn's disease, the phenomenon has been increasingly documented in the literature in the last decade. Clinicians treating Crohn's disease patients should consider this in their differential diagnosis, particularly when managing disease complications, as early detection and surgical intervention offer the best prognosis.