p-d Orbital Hybridization Engineered Single-Atom Catalyst for Electrocatalytic Ammonia Synthesis

The rational design of metal single-atom catalysts(SACs)for electrochemical nitrogen reduction reaction(NRR)is challenging.Two-dimensional metal-organic frameworks(2DMOFs)is a unique class of promising SACs.Up to now,the roles of individual metals,coordination atoms,and their synergy effect on the electroanalytic performance remain unclear.Therefore,in this work,a series of 2DMOFs with different metals and coordinating atoms are systematically investigated as electrocatalysts for ammonia synthesis using density functional theory calculations.For a specific metal,a proper metal-intermediate atoms p-d orbital hybridization interaction strength is found to be a key indicator for their NRR catalytic activities.The hybridization interaction strength can be quantitatively described with the p-/d-band center energy difference(Δd-p),which is found to be a sufficient descriptor for both the p-d hybridization strength and the NRR performance.The maximum free energy change(ΔG_(max))andΔd-p have a volcanic relationship with OsC_(4)(Se)_(4)located at the apex of the volcanic curve,showing the best NRR performance.The asymmetrical coordination environment could regulate the band structure subtly in terms of band overlap and positions.This work may shed new light on the application of orbital engineering in electrocatalytic NRR activity and especially promotes the rational design for SACs.

Manipulating d-d orbital hybridization induced by Mo-doped Co_(9)S_(8) nanorod arrays for high-efficiency water electrolysis

Precisely refining the electronic structure of electrocatalysts represents a powerful approach to further optimize the electrocatalytic performance.Herein,we demonstrate an ingenious d-d orbital hybridization concept to construct Mo-doped Co_(9)S_(8) nanorod arrays aligned on carbon cloth(CC)substrate(abbreviated as Mo-Co_(9)S_(8)@CC hereafter)as a high-efficiency bifunctional electrocatalyst toward water electrolysis.It has experimentally and theoretically validated that the 4d-3d orbital coupling between Mo dopant and Co site can effectively optimize the H_(2)O activation energy and lower H^(*)adsorption energy barrier,thereby leading to enhanced hydrogen evolution reaction(HER)and oxygen evolution reaction(OER)activities.Thanks to the unique electronic and geometrical advantages,the optimized Mo-Co_(9)S_(8)@CC with appropriate Mo content exhibits outstanding bifunctional performance in alkaline solution,with the overpotentials of 75 and 234 mV for the delivery of a current density of 10 mA cm^(-2),small Tafel slopes of 53.8 and 39.9 mV dec~(-1)and long-term stabilities for at least 32 and 30 h for HER and OER,respectively.More impressively,a water splitting electrolylzer assembled by the self-supported Mo-Co_(9)S_(8)@CC electrode requires a low cell voltage of 1.53 V at 10 mA cm^(-2)and shows excellent stability and splendid reversibility,demonstrating a huge potential for affordable and scalable electrochemical H_(2) production.The innovational orbital hybridization strategy for electronic regulation herein provides an inspirable avenue for developing progressive electrocatalysts toward new energy systems.

Intelligent Machine Learning Based Brain Tumor Segmentation through Multi-Layer Hybrid U-Net with CNN Feature Integration

Brain tumors are a pressing public health concern, characterized by their high mortality and morbidity rates.Nevertheless, the manual segmentation of brain tumors remains a laborious and error-prone task, necessitatingthe development of more precise and efficient methodologies. To address this formidable challenge, we proposean advanced approach for segmenting brain tumorMagnetic Resonance Imaging (MRI) images that harnesses theformidable capabilities of deep learning and convolutional neural networks (CNNs). While CNN-based methodshave displayed promise in the realm of brain tumor segmentation, the intricate nature of these tumors, markedby irregular shapes, varying sizes, uneven distribution, and limited available data, poses substantial obstacles toachieving accurate semantic segmentation. In our study, we introduce a pioneering Hybrid U-Net framework thatseamlessly integrates the U-Net and CNN architectures to surmount these challenges. Our proposed approachencompasses preprocessing steps that enhance image visualization, a customized layered U-Net model tailoredfor precise segmentation, and the inclusion of dropout layers to mitigate overfitting during the training process.Additionally, we leverage the CNN mechanism to exploit contextual information within brain tumorMRI images,resulting in a substantial enhancement in segmentation accuracy.Our experimental results attest to the exceptionalperformance of our framework, with accuracy rates surpassing 97% across diverse datasets, showcasing therobustness and effectiveness of our approach. Furthermore, we conduct a comprehensive assessment of ourmethod’s capabilities by evaluating various performance measures, including the sensitivity, Jaccard-index, andspecificity. Our proposed model achieved 99% accuracy. The implications of our findings are profound. Theproposed Hybrid U-Net model emerges as a highly promising diagnostic tool, poised to revolutionize brain tumorimage segmentation for radiologists and clinicians.

Morphological and molecular evidence for natural hybridization between Sorbus pohuashanensis and S. discolor (Rosaceae)

In overlapping distribution areas of Sorbus pohuashanensis and S.discolor in North China(Mount Tuoliang,Mount Xiling and Mount Baihua),Sorbus indi-viduals were found with pink fruit,which have never been recorded for the flora of China.Fourteen morphological characters combined with four chloroplast DNA markers and internal transcribed spacer(ITS)were used to analyze the origin of the Sorbus individuals with pink fruits and their relationship to S.pohuashanensis and S.discolor.PCA,SDA and one-way(taxon)ANOVA of morphological characters provided convincing evidence of the hybrid ori-gin of Sorbus individuals with pink fruits based on a novel morphological character and many intermediate characters.Haplotype analysis based on four cpDNA markers showed that either S.pohuashanensis or S.discolor were maternal parents of Sorbus individuals with pink fruits.Incongru-ence of the position of Sorbus individuals with pink fruits between cpDNA and ITS in cluster trees supported by DNA sequence comparative analysis,implying former hybridiza-tion events between S.pohuashanensis and S.discolor.Mul-tiple hybridization events between S.pohuashanensis and S.discolor might have contributed to the generation of Sorbus individuals with pink fruits.This study has provided insights into hybridization between species of the same genus in sympatric areas,which is of great significance for the study of interspecific hybridization.

Cryptic diversity and rampant hybridization in annual gentians on the Qinghai-Tibet Plateau revealed by population genomic analysis

Understanding the evolutionary and ecological processes involved in population differentiation and speciation provides critical insights into biodiversity formation. In this study, we employed 29,865 single nucleotide polymorphisms(SNPs) and complete plastomes to examine genomic divergence and hybridization in Gentiana aristata, which is endemic to the Qinghai-Tibet Plateau(QTP) region. Genetic clustering revealed that G. aristata is characterized by geographic genetic structures with five clusters(West, East, Central, South and North). The West cluster has a specific morphological character(i.e., blue corolla) and higher values of FSTcompared to the remaining clusters, likely the result of the geological barrier formed by the Yangtze River. The West cluster diverged from the other clusters in the Early Pliocene;these remaining clusters diverged from one another in the Early Quaternary. Phylogenetic reconstructions based on SNPs and plastid data revealed substantial cyto-nuclear conflicts. Genetic clustering and D-statistics demonstrated rampant hybridization between the Central and North clusters,along the Bayankala Mountains, which form the geological barrier between the Central and North clusters. Species distribution modeling demonstrated the range of G. aristata expanded since the Last Interglacial period. Our findings provide genetic and morphological evidence of cryptic diversity in G. aristata, and identified rampant hybridization between genetic clusters along a geological barrier.These findings suggest that geological barriers and climatic fluctuations have an important role in triggering diversification as well as hybridization, indicating that cryptic diversity and hybridization are essential factors in biodiversity formation within the QTP region.

Enhanced and asymmetric signatures of hybridization at climatic margins: Evidence from closely related dioecious fig species

Hybridization plays a significant role in biological evolution. However, it is not clear whether ecological contingency differentially influences likelihood of hybridization, particularly at ecological margins where parental species may exhibit reduced fitnesses. Moreover, it is unknown whether future ecosystem change will increase the prevalence of hybridization. Ficus heterostyla and F. squamosa are closely related species co-distributed from southern Thailand to southwest China where hybridization, yielding viable seeds, has been documented. As a robust test of ecological factors driving hybridization, we investigated spatial hybridization signatures based on nuclear microsatellites from extensive population sampling across a widespread contact range. Both species showed high population differentiation and strong patterns of isolation by distance. Admixture estimates exposed asymmetric interspecific gene flow.Signatures of hybridization increase significantly towards higher latitude zones, peaking at the northern climatic margins. Geographic variation in reproductive phenology combined with ecologically challenging marginal habitats may promote this phenomenon. Our work is a first systematic evaluation of such patterns in a comprehensive, latitudinally-based clinal context, and indicates that tendency to hybridize appears strongly influenced by environmental conditions. Moreover, that future climate change scenarios will likely alter and possibly augment cases of hybridization at ecosystem scales.

Cryptic divergences and repeated hybridizations within the endangered “living fossil” dove tree(Davidia involucrata) revealed by whole genome resequencing

The identification and understanding of cryptic intraspecific evolutionary units(lineages) are crucial for planning effective conservation strategies aimed at preserving genetic diversity in endangered species.However, the factors driving the evolution and maintenance of these intraspecific lineages in most endangered species remain poorly understood. In this study, we conducted resequencing of 77 individuals from 22 natural populations of Davidia involucrata, a “living fossil” dove tree endemic to central and southwest China. Our analysis revealed the presence of three distinct local lineages within this endangered species, which emerged approximately 3.09 and 0.32 million years ago. These divergence events align well with the geographic and climatic oscillations that occurred across the distributional range.Additionally, we observed frequent hybridization events between the three lineages, resulting in the formation of hybrid populations in their adjacent as well as disjunct regions. These hybridizations likely arose from climate-driven population expansion and/or long-distance gene flow. Furthermore, we identified numerous environment-correlated gene variants across the total and many other genes that exhibited signals of positive evolution during the maintenance of two major local lineages. Our findings shed light on the highly dynamic evolution underlying the remarkably similar phenotype of this endangered species. Importantly, these results not only provide guidance for the development of conservation plans but also enhance our understanding of evolutionary past for this and other endangered species with similar histories.

A new nano approach to prevent tumor growth in the local treatment of glioblastoma: Temozolomide and rutin-loaded hybrid layered composite nanofiber

Total resection of glioblastoma(GB)tumors is nearly impossible,and systemic administration of temozolomide(TMZ)is often inadequate.This study presents a hybrid layered composite nanofiber network(LHN)designed for localized treatment in GB tumor bed.The LHN,consisting of polyvinyl alcohol and core-shell polylactic acid layers,was loaded with TMZ and rutin.In vitro analysis revealed that LHN^(TMZ) and LHNrutin decelerated epithelial-mesenchymal transition and growth of stem-like cells,while the combination,LHN^(TMZ)+rutin,significantly reduced sphere size compared to untreated and LHNTMZ-treated cells(P<0.0001).In an orthotopic C6-induced GB rat model,LHNTMZ+rutin therapy demonstrated a more pronounced tumor-reducing effect than LHNTMZ alone.Tumor volume,assessed by magnetic resonance imaging,was significantly reduced in LHN^(TMZ)+rutin-treated rats compared to untreated controls.Structural changes in tumor mitochondria,reduced membrane potential,and decreased PARP expression indicated the activation of apoptotic pathways in tumor cells,which was further confirmed by a reduction in PHH3,indicating decreased mitotic activity of tumor cells.Additionally,the local application of LHNs in the GB model mitigated aggressive tumor features without causing local tissue inflammation or adverse systemic effects.This was evidenced by a decrease in the angiogenesismarker CD31,the absence of inflammation or necrosis in H&E staining of the cerebellum,increased production of IFN-γ,decreased levels of interleukin-4 in splenic T cells,and lower serum AST levels.Our findings collectively indicate that LHN^(TMZ)+rutin is a promising biocompatible model for the local treatment of GB.

Scale-space effect and scale hybridization in image intelligent recognition of geological discontinuities on rock slopes

Geological discontinuity(GD)plays a pivotal role in determining the catastrophic mechanical failure of jointed rock masses.Accurate and efficient acquisition of GD networks is essential for characterizing and understanding the progressive damage mechanisms of slopes based on monitoring image data.Inspired by recent advances in computer vision,deep learning(DL)models have been widely utilized for image-based fracture identification.The multi-scale characteristics,image resolution and annotation quality of images will cause a scale-space effect(SSE)that makes features indistinguishable from noise,directly affecting the accuracy.However,this effect has not received adequate attention.Herein,we try to address this gap by collecting slope images at various proportional scales and constructing multi-scale datasets using image processing techniques.Next,we quantify the intensity of feature signals using metrics such as peak signal-to-noise ratio(PSNR)and structural similarity(SSIM).Combining these metrics with the scale-space theory,we investigate the influence of the SSE on the differentiation of multi-scale features and the accuracy of recognition.It is found that augmenting the image's detail capacity does not always yield benefits for vision-based recognition models.In light of these observations,we propose a scale hybridization approach based on the diffusion mechanism of scale-space representation.The results show that scale hybridization strengthens the tolerance of multi-scale feature recognition under complex environmental noise interference and significantly enhances the recognition accuracy of GD.It also facilitates the objective understanding,description and analysis of the rock behavior and stability of slopes from the perspective of image data.

A Novel Approach to Breast Tumor Detection: Enhanced Speckle Reduction and Hybrid Classification in Ultrasound Imaging

Breast cancer detection heavily relies on medical imaging, particularly ultrasound, for early diagnosis and effectivetreatment. This research addresses the challenges associated with computer-aided diagnosis (CAD) of breastcancer fromultrasound images. The primary challenge is accurately distinguishing between malignant and benigntumors, complicated by factors such as speckle noise, variable image quality, and the need for precise segmentationand classification. The main objective of the research paper is to develop an advanced methodology for breastultrasound image classification, focusing on speckle noise reduction, precise segmentation, feature extraction, andmachine learning-based classification. A unique approach is introduced that combines Enhanced Speckle ReducedAnisotropic Diffusion (SRAD) filters for speckle noise reduction, U-NET-based segmentation, Genetic Algorithm(GA)-based feature selection, and Random Forest and Bagging Tree classifiers, resulting in a novel and efficientmodel. To test and validate the hybrid model, rigorous experimentations were performed and results state thatthe proposed hybrid model achieved accuracy rate of 99.9%, outperforming other existing techniques, and alsosignificantly reducing computational time. This enhanced accuracy, along with improved sensitivity and specificity,makes the proposed hybrid model a valuable addition to CAD systems in breast cancer diagnosis, ultimatelyenhancing diagnostic accuracy in clinical applications.

Asymmetric orbital hybridization in Zn-doped antiperovskite Cu_(1-x)Zn_(x)NMn_(3)enables highly efficient electrocatalytic hydrogen production

Rational design of efficient and robust earth-abundant alkaline hydrogen evolution reaction(HER)catalysts is a key factor for developing energy conversion technologies.Currently,antiperovskite nitride CuNMn_(3)has garnered significant interest due to its remarkable properties such as negative/zero thermal expansion and magnetocaloric effects.However,when utilized as hydrogen evolution catalysts,it encounters large challenge resulting from excessively strong/weak interactions with adsorbed H on Mn/Cu active sites,which leads to low HER activity.In this study,we introduce an asymmetric orbital hybridization strategy in Zn-doped Cu_(1-x)Zn_(x)NMn_(3)by leveraging the localization of Zn electronic states to reconfigure the electronic structures of Cu and Mn,thereby reducing the energy barrier for water dissociation and optimizing Cu and Mn active sites for hydrogen adsorption and H_(2)production.Electrochemical evaluations reveal that Cu_(0.85)Zn_(0.15)NMn_(3)with x=0.15 demonstrates exceptional electrocatalytic activity in alkaline electrolytes.A low overpotential of 52 mV at 10 mA cm^(-2)and outstanding stability over a 150-h test period are achieved,surpassing commercial Pt/C.This research offers a novel strategy for enhancing HER performance by modulating asymmetric hybridization of electron orbitals between multiple metal atoms within a material structure.

Enhanced Redox Electrocatalysis in High‑Entropy Perovskite Fluorides by Tailoring d–p Hybridization

High-entropy catalysts featuring exceptional properties are,in no doubt,playing an increasingly significant role in aprotic lithium-oxygen batteries.Despite extensive effort devoted to tracing the origin of their unparalleled performance,the relationships between multiple active sites and reaction intermediates are still obscure.Here,enlightened by theoretical screening,we tailor a high-entropy perovskite fluoride(KCoMnNiMgZnF_(3)-HEC)with various active sites to overcome the limitations of conventional catalysts in redox process.The entropy effect modulates the d-band center and d orbital occupancy of active centers,which optimizes the d–p hybridization between catalytic sites and key intermediates,enabling a moderate adsorption of LiO_(2)and thus reinforcing the reaction kinetics.As a result,the Li–O2 battery with KCoMnNiMgZnF_(3)-HEC catalyst delivers a minimal discharge/charge polarization and long-term cycle stability,preceding majority of traditional catalysts reported.These encouraging results provide inspiring insights into the electron manipulation and d orbital structure optimization for advanced electrocatalyst.

Aqueous Supercapacitors With Wide Operative Voltage Window and Long Cycling Life Enabled by Electrolyte Hybridization Effect

Developing supercapacitors(SCs)with long cycling life and wide operative voltage window is a significant topic in the field of aqueous electrolytes.Although the design of water in salt(WIS)electrolytes has pushed the development of aqueous electrolytes to a new height,the WIS electrolytes with an operative voltage window of up to 2.5 V is still very scarce.Herein,in order to enrich the type of aqueous electrolyte with high operative voltage,tetramethylammonium trifluoromethanesulfonate(TMAOTf)based WIS electrolyte was used as a model to construct WIS based hybrid electrolyte with acetonitrile(ACN)co-solvent and LiTFSI co-solute.In view of the coordination effect of ACN and Lit on free water in TMAOTf based WIS electrolyte,the TMAt-Lit-AWIS electrolyte has the electrochemical stabilization window of up to 3.35 V.Further coupled with the commercial YP-50F electrodes,TMAt-Lit-AWIS based SCs exhibited wide operative voltage window(2.5 V),long cycling life(45,000 cycles)and good low-temperature performance(99.99%capacitance retention after 2000 cycles at20℃).The design of this hybrid electrolyte will enrich the types of aqueous hybrid electrolytes with long cycling life and wide operative voltage window.

Advancements in Liver Tumor Detection:A Comprehensive Review of Various Deep Learning Models

Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment planning.Liver Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and challenging.This review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and resilience.Performance metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical contexts.The review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging conditions.It suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular methods.This paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.

Enhancing ^(*)CO coverage on Sm-Cu_(2)O via 4f-3d orbital hybridization for highly efficient electrochemical CO_(2) reduction to C_(2)H_(4)

The electrocatalytic conversion of CO_(2) into valuable chemical feedstocks using renewable electricity offers a compelling strategy for closing the carbon loop.While copper-based materials are effective in catalyzing CO_(2) to C_(2+)products,the instability of Cu^(+)species,which tend to reduce to Cu~0 at cathodic potentials during CO_(2) reduction,poses a significant challenge.Here,we report the development of SmCu_(2)O and investigate the influence of f-d orbital hybridization on the CO_(2) reduction reaction (CO_(2)RR).Supported by density functional theory (DFT) calculations,our experimental results demonstrate that hybridization between Sm^(3+)4f and Cu^(+)3d orbitals not only improves the adsorption of *CO intermediates and increases CO coverage to stabilize Cu^(+) but also facilitates CO_(2) activation and lowers the energy barriers for CAC coupling.Notably,Sm-Cu_(2)O achieves a Faradaic efficiency for C_(2)H_(4) that is 38%higher than that of undoped Cu_(2)O.Additionally,it sustains its catalytic activity over an extended operational period exceeding 7 h,compared to merely 2 h for the undoped sample.This research highlights the potential of fd orbital hybridization in enhancing the efficacy of copper-based catalysts for CO_(2)RR,pointing towards a promising direction for the development of durable,high-performance electrocatalysts for sustainable chemical synthesis.

ACTIVATION OF NUCLEOLAR rRNA GENE TRANSCRIPTION IN LYMPHOCYTES BY TUMOR PROMOTERS: APPLIES STUDIES WITH IN SITU HYBRIDIZATION DETECTED BY FLUORESCENT METHOD

The distribution of rDNA was visualized in interphase nuclei of tumor promoter treated human lymphocytes in comparison with the mltogen Phytoheamagglutinin (PHA) effects by using an in situ hybridization fluorescent method. The procedure involves biotinylated rDNA as the probe and FITC-avidin as detection system. Silver (Ag) staining was used to visualize nucleoli. In the interphase nuclei of most of the nonstimulated control lymphocytes, only one small Ag-stained nucleolus could be seen. The in situ hybridization, however, revealed one to several agglomerations of rDNA fluorescent spots. With tumor promoting herb extract WCE (40 μg/ml) or TPA (60 ng/ ml) treatment, the Interphase nucleoli increased slightly in number with the morphology alteration into larger, reticular or compact granular types. Ag-stained particles also increased in number. The number of the in situ hybridization rDNA fluorescent spots and dots increased markedly and largereticulate formations of numerous rDNA spots were seen. This phenomenum resembles to the changes in PHA stimulated lymphocytes. Statistic analysized data showed signifcant difference between control and drug- treated cells. These results indicate that transcriptionally activated rDNA and amplification of total rDNA was induced by the used tumor promoters.

Scoring system supporting suture decision-making for duodenal submucosal tumors

BACKGROUND In recent years,endoscopic resection(ER)has been employed for the excision of submucosal tumors(SMTs).Nonetheless,ER in the duodenum is linked to ele-vated risks of both immediate and delayed hemorrhagic complications and perforations.Satisfactory suturing is crucial for reducing the occurrence of complications.AIM To establish a clinical score model for supporting suture decision-making of duodenal SMTs.METHODS This study included 137 individuals diagnosed with duodenal SMTs who under-went ER.Participants were evenly divided into two groups:A training cohort(TC)comprising 95 cases and an internal validation cohort(VC)with 42 cases.Subsequently,a scoring system was formulated utilizing multivariate logistic regression analysis within the TC,which was then subjected to evaluation in the VC.RESULTS The clinical scoring system incorporated two key factors:Extraluminal growth,which was assigned 2 points,and endoscopic full-thickness resection,which was given 3 points.This model demonstrated strong predictive accuracy,as evidenced by the area under the receiver operating characteristic curve of 0.900(95%confidence interval:0.823-0.976).Additionally,the model’s goodness-of-fit was validated by the Hosmer-Lemeshow test(P=0.404).The probability of purse-string suturing in low(score 0-2)and high(score>3)categories were 3.0%and 64.3%in the TC,and 6.1%and 88.9%in the VC,respectively.CONCLUSION This scoring system may function as a beneficial instrumentality for medical practitioners,facilitating the decision-making process concerning suture techniques in the context of duodenal SMTs.

Hepatic hemangiomas mimicking gastrointestinal stromal tumors: A case report

BACKGROUND Hepatic hemangiomas can be challenging to diagnose,particularly when they present with atypical features that mimic other conditions,such as gastrointestinal stromal tumors(GISTs).This case highlights the diagnostic difficulties encountered when imaging subepithelial lesions,especially when conventional methods such as computed tomography(CT)and endoscopic ultrasound(EUS)are used.CASE SUMMARY A 44-year-old woman presented with intermittent abdominal distension and heartburn for three months.Her medical history included iron deficiency anemia,menorrhagia,and previous cholecystectomy.One week prior to admission,an endoscopy suggested a bulging gastric fundus,which was likely a GIST,along with chronic nonatrophic gastritis and bile reflux.CT and EUS revealed nodules in the gastric fundus,which were initially considered benign tumors with a differential diagnosis of stromal tumor or leiomyoma.During surgery,unexpected lesions were found in the liver pressing against the gastric fundus,leading to laparoscopic liver resection.Postoperative pathology confirmed the diagnosis of hepatic cavernous hemangiomas.The patient recovered well and was discharged five days later,with normal follow-up results at three months.CONCLUSION This case underscores the challenges in the preoperative diagnosis of GISTs,particularly the limitations of the use of CT and EUS for the evaluation of subepithelial lesions.While CT is the primary tool for visualizing abdominal tumors,it is difficult to detect smaller lesions and assess the layers of the gastrointestinal wall on CT.EUS is recommended for the evaluation of nodules smaller than 2 cm and is useful for distinguishing GISTs from other lesions;however,its accuracy with regard to the differential diagnosis is relatively low.In this case,the gastric distension observed on imaging led to the compression of a liver tumor against the stomach,resulting in the misinterpretation of the tumor as a gastric wall lesion.

Innovative approaches in predicting outcomes for rectal neuroendocrine tumors

Rectal neuroendocrine neoplasms pose significant challenges due to their varied presentations and prognoses.Traditional prognostic models,while useful,often fall short of accurately predicting clinical outcomes for these patients.This article discusses the development and implications of a novel prognostic tool,the GATIS score,which aims to enhance predictive accuracy and guide treatment strategies more effectively than current methods.Utilizing data from a large cohort and employing sophisticated statistical models,the GATIS score integrates clinical and pathological markers to provide a nuanced assessment of prognosis.We evaluate the potential of this score to transform clinical decision-making processes,its integration into current medical practices,and future directions for its develo-pment.The integration of genetic markers and other biomarkers could further refine its predictive power,highlighting the ongoing need for innovation in the management of rectal neuroendocrine neoplasms.

Precision oncology: The role of minimally-invasive ablation therapy in the management of solid organ tumors

Solid organ tumors present a significant healthcare challenge,both economically and logistically,due to their high incidence and treatment complexity.In 2023,out of the 1.9 million new cancer cases in the United States,over 73%were solid organ tumors.Ablative therapies offer minimally invasive solutions for malignant tissue destruction in situ,often with reduced cost and morbidity compared to surgical resection.This review examines the current Food and Drug Administration-approved locoregional ablative therapies(radiofrequency,microwave,cryogenic,high-intensity focused ultrasound,histotripsy)and their evolving role in cancer care.Data were collected through a comprehensive survey of the PubMed-inde-xed literature on tumor ablation techniques,their clinical indications,and outco-mes.Over time,emerging clinical data will help establish these therapies as the standard of care in solid organ tumor treatment,supported by improved long-term outcomes and progression-free survival.