Reductive soil disinfestation (RSD) is a soil remediation technology that effectively inhibits the transfer and spread of antibiotic resistance genes (ARGs) in soil. However, in soil contaminated with varying concentrations of oxytetracycline (OTC), the effect of RSD technology on OTC and ARGs remains unknown. In the laboratory, we established three soil treatments: OS (original soil samples); Soil Cultivation (control soils with five different residual concentrations of OTC (0, 5, 20, 50, 100 mg/kg)); RSD (treated soils with five different residual concentrations of OTC incubated at a constant temperature of 37 °C for 30 days). Results indicated that RSD can effectively degrade the concentration of OTC in soil, with degradation rates ranging from 22.91% to 82.83%. Additionally, RSD significantly reduced the relative abundance of ARGs, mobile genetic elements (MGEs) (P < 0.05), with reduction rates ranging from 24.39% to 86.56%. Network analysis indicated that Microbispora and Clostridium are the main potential hosts of ARGs. Redundancy analysis suggested that MGEs (42.7%) and microbial communities (19.5%) are the primary factors contributing to changes in ARGs. Therefore, the inhibition of MGEs abundance and reduction of host bacteria abundance by RSD are the primary mechanisms for reducing ARGs. In summary, RSD shows the potential for removing OTC and inhibiting the spread of ARGs in soil. This study provides a theoretical basis for using RSD in remediation of agricultural soils contaminated with antibiotics.

Abstract Background: Oncocytic (Hurthle) cell neoplasms (OCNs) of the thyroid are follicular-derived lesions characterized by abundant eosinophilic cytoplasm due to mitochondrial accumulation. Fine-needle aspiration (FNA) cytology is a primary diagnostic tool for thyroid nodules but struggles to distinguish benign from malignant OCNs, leading to potential overtreatment. Identifying preoperative predictors of malignancy may improve risk stratification. Methods: A retrospective review was conducted at Chi Mei Medical Center from January 2012 to December 2023. Patients with a FNA diagnosis of OCN and subsequent thyroidectomy were included. Demographic data, ultrasound characteristics (tumor size and TIRADS classification), and final histopathological diagnoses were analyzed. Logistic regression models assessed predictors of malignancy (P < 0.05). Results: Of 1998 patients with thyroid nodules exhibiting oncocytic features on FNA, 174 met the inclusion criteria. Malignancy was confirmed in 28 cases (16.1%), with oncocytic carcinoma accounting for 21% of malignant cases. Gender and TIRADS classification were not significantly associated with malignancy risk. Tumor size was a significant predictor, with a cutoff of 1.83 cm demonstrating an adjusted odds ratio (AOR) of 4.22 (95% CI: 1.18–15.09, P = 0.0268) for malignancy. Conclusion: Preoperative differentiation between benign and malignant OCNs remains challenging. Smaller tumor size is associated with a significant risk of malignancy. Given their potential for distant metastasis and resistance to radioactive iodine therapy, diagnostic lobectomy remains the preferred approach for the management of OCNs. Keywords: Oncocytic cell, Hurthle cell, thyroid Key points 1. FNA remains a crucial preoperative tool for evaluating thyroid nodules, though distinguishing benign from malignant oncocytic neoplasms can be challenging. 2. Histopathologic evaluation is essential for definitive diagnosis, as cytologic findings alone may not reliably predict malignancy. 3. Risk stratification plays a key role in shared decision-making, helping patients and clinicians choose between lobectomy and total thyroidectomy when FNA reveals an oncocytic cell neoplasm. 4. Oncocytic cell carcinoma has a poor prognosis due to its high recurrence rate and poor response to radioactive iodine therapy. 5. This study provides insights into the correlation between FNA findings and final pathologic outcomes, supporting more informed clinical decision-making.

Abstract Introduction Chronic rhinosinusitis (CRS) is phenotypically classified into Chronic rhinosinusitis with or without nasal polyposis, CRSwNP and CRSsNP, respectively. Many treatment modalities exist for CRSwNP such as corticosteroids, among others. Despite the advancements in medical management, surgical procedures such as Endoscopic Sinus Surgery (ESS) are still required, especially for cases where medical managements alone is not sufficient. This study aims to evaluate the efficacy of different postoperative medical regimens given after functional endoscopic sinus surgery. Methods 144 patients who underwent Functional Endoscopic Sinus Surgery (FESS) in 4 different clinics and had CRSwNP were recruited. All patients underwent clinical, laboratory and radiological tests. Patients were grouped into 5 groups based on presence of eosinophilia, AERD, chances of recurrence, and clinical/radiological severity. The aggressiveness of the treatment increases as you go up the groups, with group 1 receiving the least aggressive treatment. Results In this prospective cohort study, most of the patients were female (52.1%) and their ages ranged from 21-73 years old, with a mean of 37.4±10.7 years old. The recurrence rate after 2 years following surgery increases from 0% in Group 1, to 33.3% in Group 5. Conclusion Many strategies can be pursued to decrease the recurrence of CRSwNP following ESS. These include extensive preoperative patient preparation, delicate removal of all cells during endoscopic sinus surgery and a postoperative medical regimen tailored to the severity of the disease that requires complete adherence. Furthermore, it is essential to consider all hidden anatomical spaces during ESS.

IntroductionDermatological infections form the major chunk of disease at poor household (Afsar 2010) level contributing in the shuddering of humanity. In such localities, the skin infectious diseases that are most prevalent include Scabies, Warts, Molluscum Contagiosum, Tinea pedis, Tinea Corporis, Ringworm, Candidiasis, Cellulitis and Folliculitis. Besides poverty, the lack of knowledge and unsatisfactory sanitary and hygienic conditions work as the contributory factors in propagation aggravation of the diseases. This research entails a complete study of the risk factor, transmission factors and control on skin infections among different age and gender groups.

The natural uranium isotope ratio of 234U/238U in seawater behaves conservatively at basin scale, yet it can be regionally affected by local continental freshwater discharge at decadal to centennial timescales. Here, we analyse annual variations in the 234U/238U isotope ratio, expressed as ‰-deviation from radioactive equilibrium as δ234U, of a coral from Cuba. Over the past 237 years, the mean δ234U value of the coral was 145.58 ± 0.1 ‰, which is identical to that of modern open ocean seawater, whereas the average variation over the past century has been ± 3.7 ‰. This moderate variability is, however, significantly greater than the external precision and reproducibility of measurements of ± 0.55 ‰. Moreover, the δ234U values coincide inversely with regional precipitation, suggesting excess 234U contribution from regional freshwater runoff. The most important finding, is a strong increase in annual δ234U variability to ± 8,1 ‰ during the end of the Little Ice Age (LIA, 1778–1847). We suggest that the increased δ234U dynamics reflect substantial excess 234U contributions from the Mississippi, far greater variability in the local freshwater fluxes to the Gulf of Mexico, and/or reduced advective currents during the LIA. This study demonstrates that yet unexplored variability in coral δ234U records within the presently known range of global seawater δ234U may be attributed to local and advected freshwater sources, which opens a new pathway for reconstructing these processes over time; moreover, it places strong constraints on the initial δ234U variability of fossil corals in light of ultrahigh-precision 230Th/U dating.

1. IntroductionSoil constraints, such as sodicity, salinity, acidity, alkalinity and nutrient imbalances, are key factors limiting crop yields and affecting the sustainability of farming practices in Australia and globally (Dang et al., 2010a; Dang & Moody, 2016; Ulfa et al., 2022). Identifying and managing these constraints are crucial for optimizing agricultural productivity and ensuring food security. Soil chemical properties such as nitrate (NO3– ), electrical conductivity (ECe), pH, chloride (Cl), exchangeable sodium percentage (ESP), the concentrations of exchangeable Ca (ECa), K (EK), and Mg (EMg), have a significant impact on soil health and crop productivity (Alotaibi et al., 2023; Garello et al., 2023; González-Orozco et al., 2024; Meena et al., 2023; Rao et al., 2023). NO3– is essential for plant growth, providing readily available nitrogen (N) for uptake. However, imbalances in the N forms may affect the N cycle in ecosystems, leading to environmental issues such as leaching, acidification and volatilization, ultimately reducing N-use efficiency and causing nutrient losses (Tilman et al., 2002). ECe serves as a crucial indicator of soil health, reflecting the soil salinity levels and overall soil fertility. High ECe values typically indicate higher salinity, which could hinder plant growth, limiting water availability to plants and reducing crop yields (Rengasamy, 2006). Soil pH indicates soil acidity or alkalinity, with extreme pH levels potentially restricting the availability of essential nutrients like P, Ca, and Mg, while also causing toxicity of certain elements like Na, Al and Mn (Fageria & Baligar, 2008; Naorem et al., 2023; Orton et al., 2018; Ulfa et al., 2023). Chloride could impact plant health, particularly in sensitive crops, causing leaf burn and reduced photosynthesis (Bhoite et al., 2024; Munns & Tester, 2008). EK is vital indicators of soil health due to its role as a K reserve, whereas ECa and EMg are associated with poor soil health and an increased risk of dispersion. These exchangeable forms reflect the soil’s ability to retain essential nutrients necessary for plant growth and soil health. ECa is crucial for soil aggregation and root development, EK supports enzyme activity and stomatal water regulation, and appropriate EMg is important for crop quality, being a core component of chlorophyll and involved in enzyme activation (Naorem et al., 2023; Tiwari et al., 2020). Therefore, ECa, EK, and EMg are critical for both soil physical health and crop nutrition (Simoniello et al., 2022).Soil sampling and testing remain a critical step in assessing soil health and identifying constraints. Traditional methods involve collecting soil samples from various depths and analyzing them for key indicators such as available N (NO3– ), salinity (ECe), pH, Cl, and exchangeable cations. These indicators provide valuable insights into the soil’s fertility status and potential constraints. Studies have indicated that analyzing soil N parameters, such as NO3– , could help understand N cycle dynamics (Camargo & Alonso, 2006; Cookson et al., 2006; Das et al., 2024), while an ECe of 4 dS/m or higher in the soil saturation extract could indicate salinity, which could negatively impact crop production (Rengasamy, 2006). High Cl concentrations and sodicity in the subsoil have been identified as significant constraints that reduce water availability and crop yields in Australia’s northern grains region, with subsoil Cl proving to be a more reliable indicator of reduced water extraction and grain yields than salinity or ESP (Dang et al., 2011a; Dang et al., 2011b). Additionally, high ESP and EMg can cause soil dispersion, further compromising soil structure and crop productivity.Remote sensing technologies have revolutionized the identification of soil constraints. Tools like ConstraintID (https://constraintid.net.au/) utilizes satellite imagery to calculate enhanced vegetation indices (EVI), which reflect the peak greenness of fields (Ulfa et al., 2023). Higher EVI indicates more biomass, and consequently, likely higher yield (Orton et al., 2022; Ulfa et al., 2023). The EVI data, together with ground truthing, can be used to stratify agricultural land into consistently high (H), consistently low (L), and inconsistent (I) productivity zones. Such stratification supports targeted soil sampling and the identification of management zones to address specific soil constraints.We examine the differences in soil indicators across three productivity zones (H: consistently high yield, I: inconsistent yield, L: consistently low yield) and five soil depth layers (0-120 cm, D1-D5) at 21 sampling locations within Queensland, Australia. By analyzing these differences, we seek to identify the soil conditions that drive variations in EVI and impact crop yield. We hypothesize that significant differences in soil indicators (NO3– , ECe, pH, Cl, ESP, ENa, ECa, EK, EMg) exist between the three productivity zones within each soil layer (D1-D5) and that specific indicators are more strongly associated with observed differences in crop yield across these zones. To achieve this aim, the study addresses the following objectives: i) to assess the differences in soil indicators in various soil layers among the three productivity zones, ii) to associate particular soil constraints with the observed differences in crop yield among the three zones, and iii) to identify variations in soil constraints across different soil layers. This should help to clarify the implications of such variations in soil constraints have for soil management practices. Understanding the specific soil constraints that impact crop yield is essential for developing effective soil management strategies which will support optimal plant growth and maximize its yield potential.

Using computer-based digital image processing technology to conduct micro-description and quantitative characterization of rock features forms the foundation of geological data digitization. While rock image analysis under microscopes and with higher precision has progressed rapidly, image processing for field outcrops has received little attention. This paper takes clastic rocks as an example and explains techniques for processing petrological images from field outcrops. To address the issue of oversimplified quantitative representation of rock features, methods are explored in three areas: image denoising, morphological processing, and image segmentation. By linking the lithology of clastic rocks to their colors, a "penalty and reward scoring mechanism" algorithm is introduced, and 14 lithology classification situations based on color are summarized. A region-growing algorithm is also applied to accurately identify special minerals such as iron and brass. Edge detection, watershed algorithms, and other morphological techniques are then performed on the field images, followed by color-based particle labeling and calculation of related morphological parameters. The Folk-Ward formula is improved to analyze grain size results. Fractures and pores are quantitatively characterized next. Fractures are extracted automatically using morphological processing and adaptive binarization, with interactive computation of fracture lengths. The maximum internal tangent circle algorithm calculates the maximum fracture width. Connected regions are filtered based on color, size, and solidity to extract pores, allowing the area, perimeter, and circularity to be computed. The experimental results demonstrate that systematic use of computer image processing enables multi-dimensional feature extraction of field clastic rocks, thereby improving the efficiency of geological fieldwork.  Keywords ---Rock physics, Theory, Data processing, Computing aspects, Interpretation

Abstract

Increasing evidence suggests that invasive plants can sustain high growth rates in heavy metal-enriched environments, while native species do not contribute to their invasion success. However, the underlying mechanisms are poorly understood. This study examined the invasive plant Phytolacca americana and native Phytolacca acinosa in Cd-contaminated soils in China. The results showed that, while native plant biomass decreased at higher soil Cd concentrations, invasive plant biomass remained unaffected. Soil enzyme activities decreased with increasing Cd concentration but were higher in soils where invasive plants grew than those in soils where native plants grew. Phytolacca americana accumulated more Cd, particularly in the leaves and under higher soil Cd concentrations. Native seed germination was inhibited with increasing litter-Cd concentration, whereas invasive seed germination was unaffected. These findings suggest that the ability of the invasive species to mitigate the negative effects of Cd pollution on soil enzyme activities contributed to their higher Cd-tolerance by maintaining soil nutrient availability. Additionally, higher leaf-Cd levels in invasive plants constitute an elemental defence. Overall, heavy metal pollution not only favoured invasive plants by suppressing native plant growth but may have also promoted invasion through the effects of Cd accumulation in invasive litter on native seed germination.

RATIONALE: The conventional method for measuring carbon and oxygen isotopes in carbonates involves the reaction of carbonate minerals with phosphoric acid (PPA) to generate CO 2, followed by purification and isotopic analysis. During this reaction, a temperature-dependent oxygen isotope acid fractionation factor (AFF) is introduced, as not all oxygen is released in CO 2. While the temperature dependence of AFF has been extensively studied in pure carbonate minerals, little research has been conducted on AFF variations in mixed carbonate minerals with diverse chemical and mineralogical compositions. This study aims to investigate the range of AFF variations in carbonates containing multiple mineral phases. METHODS: Oxygen isotope compositions of CO 2 produced from CaCO 3-MgCO 3 mixed minerals reacting with PPA at 25℃, 50℃, 70℃, 90℃ were analyzed using a GasBench II system coupled with a Thermo Finnigan Delta V Plus isotope ratio mass spectrometer. RESULTS: The AFF values for CaCO 3-MgCO 3 mixed minerals fall between those of pure calcite and dolomite, generally aligning with theoretical predictions. Additionally, the fractionation gradient (dδ 18O/dT -1) increases with rising Mg/Ca ratio and dolomite content, indicating a systematic trend in fractionation behavior. CONCLUSIONS: These findings provide a framework for AFF correction based on Mg/Ca ratio or dolomite content, enhancing the reliability and precision of oxygen isotope measurements in natural impure carbonates.

In Hamilton-Jacobi reachability analysis, reachable sets are characterised by sublevel sets of the value function of an optimal control problem. Although grid-based approaches provide a general-purpose means of numerically computing this value function, the curse-of-dimensionality often limits their use in all but simple applications. In this paper, inner-approximations of the backwards reachable set are characterised through the design of a feedback control law for feedback linearisable systems subject to input constraints. This structure is exploited to propose a selection of control gains via an optimisation problem. The computational cost and memory requirement of the proposed scheme are tied to the number of system states in a polynomial manner. Thus, the proposed approximation scheme is computationally tractable for feedback linearisable systems of relatively high dimension.

A phytochemical study of corn silk resulted in the isolation of nine novel β-macrocarpene-type sesquiterpenoids ( 1– 9) along with one known analogue ( 10). The structural elucidation of these compounds was accomplished using comprehensive spectral data, X-ray crystallography, and electronic circular dichroism (ECD) calculations. Bioassay revealed that at a concentration of 20 μg/g, compounds 2, 3, 6, and 7 significantly reduced the weight of Spodoptera frugiperda, 4 inhibited the growth of S. litura, whereas compound 10 inhibited weight of both insects. In vitro enzyme assays showed that compound 10 inhibited carboxylesterase (CarE) and glutathione S-transferase (GST) enzyme activities in S. litura but did not impact these enzymes in S. frugiperda. Furthermore, transcriptome analysis suggested that 10 can upregulate the expression of the cytochrome P-450 monooxygenase (CPY450) and GST genes in S. frugiperda, whereas increased expression of carcinine transporter-like gene and decreased expression of trypsin were observed in S. litura. Overall, this research reveals the potential of corn sesquiterpenoids for developing environmentally friendly insecticides.

Table 1 Soluble fraction (%) of SPI peptides obtained at different gastric and gastroduodenal residence times

Chronic inflammatory dermatoses (CIDs), such as psoriasis, atopic dermatitis, and lichen planus, are characterized by persistent inflammation and immune dysregulation. Current treatments primarily target inflammatory pathways but often fail to achieve sustained remission. We propose that hyaluronic acid (HA), a key component of the extracellular matrix, plays a significant immunomodulatory role in CIDs. Specifically, the molecular weight of HA influences its interaction with immune receptors, modulating inflammatory responses. High-molecular-weight HA (HMW-HA) may exhibit anti-inflammatory properties by engaging CD44 receptors, leading to the suppression of pro-inflammatory cytokines. Conversely, low-molecular-weight HA (LMW-HA), resulting from tissue injury or degradation, may act as a damage-associated molecular pattern (DAMP), activating Toll-like receptors (TLR2 and TLR4) and promoting inflammation. This dualistic role of HA suggests that modulating its molecular weight distribution in the skin could offer a novel therapeutic approach for CIDs. Future research should focus on elucidating the mechanisms underlying HA's size-dependent effects on immune cells and exploring HA-based interventions to restore immune balance in CIDs.

Reverse vaccinology approach is an in silico methodology in order to identify antigens that are good vaccine candidates in a simple, safety and inexpensive way, with reduced time and effort. This strategy is based on bioinformatics tools, which predict important protein structural features, such as: integral transmembrane β-barrel arrangements; transmembrane alpha-helices; signal peptides; and secreted proteins. In this context, specific tools have been developed for the prediction of critical structural features, however despite significant progress, challenges persist due to the lack of integration in existing methods and the limited robustness and generalization of deep learning models with sparse data. To address these gaps, we introduce ReVarcine, a transformer-based deep neural network designed to automate the identification of signal peptides, subcellular localization, β-barrels, and alpha helices in bacteria, while prioritizing vaccine targets, advancing immunoinformatics and next-generation vaccine development. ReVarcine integrates predictions of signal peptides, subcellular localization, and structural features into a single automated workflow, generating detailed reports and prioritizing vaccine targets. Benchmarks against SignalP, PSORT, and PSIPRED demonstrate its superior predictive capabilities across diverse proteomes. By addressing key limitations in immunoinformatics, ReVarcine sets a new standard for computational tools in immunology and vaccinology, with potential for significant contributions through ongoing refinement and experimental validation.

Species’ geographic distributions are central to research in biogeography, macroecology, and conservation biology. However, incomplete or inaccurate knowledge about their spatiotemporal ranges—known as the Wallacean shortfall—hampers our understanding of biodiversity patterns and processes. In this study, we systematically reviewed 192 papers that reported new distribution records of China’s mammals from 2001 to 2023, covering 150 species in 26 families across 7 orders. We examined the taxonomic, spatiotemporal, and biogeographic characteristics of these newly recorded species. We used Bayesian Phylogenetic Generalized Linear Mixed Models (PGLMM) to assess how intrinsic traits and extrinsic factors influenced the likelihood of discoveries and partial Poisson regressions to evaluate how species-level attributes, environmental and socio-economic factors shaped the number of new occurrence records across provinces. Our results showed that Chiroptera (n=69), Eulipotyphla (n=26) and Rodentia (n=23) had the highest number of new records. Among provinces, Yunnan (n=31), Guangdong (n=22), and Xizang (n=18) yielded the most new records. The amount of annual discoveries varied and peaked between 2017 and 2021. The Western Mountain and Plateau (n=39) and the East Hilly Plain (n=33) zoogeographic subregions had the greatest number of newly recorded species. Notably, 61 (40.7%) species were found to extend towards the north or northeast of their known ranges, and 32 (21.3%) eastward, mainly due to the sampling bias. Smaller-bodied species and those with broader habitat ranges are more likely to yield new records, and the total number of new records was positively correlated with regional species richness and current survey efforts (r > 0.5, p < 0.05). These findings expand the known distributions of China’s mammals and provide essential data for mitigating the Wallacean shortfall. They underscore the urgent need for intensified surveys in biodiversity-rich, underexplored regions—especially targeting small-bodied, data-deficient taxa—and for timely updates and data-sharing to better inform conservation strategies.

The genus Strobilurus is prevalent in the Himalayan temperate forests of Pakistan, with sporocarps collected from the Hindukush region. Extensive field surveys spanning five years (2018-2022) were conducted in these locales, resulting in multiple collections of the present specimen. Identification of the specimen was accomplished through comprehensive morphological, anatomical, and molecular analyses. The primary macro- and micro-morphological characteristics of the Pakistani collection include a flat pileus with a rimose margin, varying from yellow to dark-yellow in color, free lamellae, strigos, smooth and reddish stipe, ovoid to ellipsoid basidiospores with a rounded apex, guttulate basidia bearing 2-3 sharp sterigmata, fusoid-ampullaceous cheilocystidia, fusoid-ventricose pleurocystidia, conical and thick-walled hyaline pilipellis, and branched and gutulllated stipitipellis. Morphological, molecular, and phylogenetic analyses collectively confirm the specimen’s identity as Strobilurus albipilatus, marking a new record for Pakistan.

The Infinite Principle establishes that whenever an option has unbounded upside and bounded downside, pursuing it is not just reasonable—it is mathematically required. Rooted in expected value theory, the principle proves that any decision meeting these conditions dominates all finite alternatives.This paper derives the Infinite Principle rigorously, addresses key objections, and demonstrates its universal applicability across domains such as venture capital, existential risk mitigation, and technological innovation. Optimism, long considered a bias, emerges as the only rational stance in decisions where potential is limitless.The conclusion is inescapable: when unbounded opportunity exists, rejecting it in favor of finite caution is a systematic error. Rejecting infinite potential is not caution—it is miscalculation. Rationality demands we embrace the infinite.

Cancer is not just a mass to remove—it is genomic disorder accumulating faster than it can be repaired. This essay reframes oncology as debugging rather than deletion: measure instability as a composite entropy index, track its rate of change, and modulate three levers—damage rate, repair capacity, and selection pressure. We pair anatomical staging (I–IV) with genomic instability to avoid conflating tumor location with system disorder. The framework is falsifiable: it fails if cancers arise without rising entropy or if entropy metrics lack predictive value. We present a mechanistic model, observable proxies, and testable predictions for those seeking to move beyond reactive elimination toward proactive stabilization.

The Black Swan theory mistakes gaps in knowledge for inherent randomness. "Unpredictable" events are not cosmic anomalies but reflections of observer ignorance. This paper introduces the Blind Turkey Principle, demonstrating that unpredictability is not a feature of reality but a failure to recognize system drivers. By analyzing historical case studies, we show that Black Swans dissolve when viewed with sufficient understanding. The illusion of unpredictability stems not from the events themselves but from the limits of the observer’s knowledge. True resilience is not about bracing for chaos but eliminating ignorance—transforming Black Swans into White Swans through directional mastery.

Fire ends when oxygen is removed, war ends when logistics are removed. Battles may be won or lost, but the outcome is decided by whether forces can be sustained. Destroying supply is always cheaper and more decisive than destroying strength: without fuel armies cannot move, without food they cannot endure, without materiel they cannot fight. This is the Law of Oxygen: control logistics and you control capability; deny logistics and you deny options. All else is tactics. 

Background: Congenital thrombotic thrombocytopenic purpura (cTTP) is a rare disorder caused by biallelic mutations in the ADAMTS13 gene, leading to recurrent microangiopathic hemolytic anemia and thrombocytopenia. Due to its rarity, cTTP is frequently misdiagnosed as immune thrombocytopenia (ITP) or other hematologic disorders, delaying appropriate management. Case Report: We describe a 16-year-old Indian girl with a history of multiple episodes of thrombocytopenia, anemia, and heavy menstrual bleeding. Initially diagnosed and treated as ITP, she presented with left-sided hemiparesis, thrombocytopenia, and anemia. Laboratory investigations revealed severely deficient ADAMTS13 activity (2.7%) with absent ADAMTS13 antibodies, suggestive of cTTP. Genetic analysis confirmed compound heterozygous mutations in ADAMTS13 (c.2317C>T, p.Gln773Ter in exon 19 and c.1337T>C, p.Met446Thr in exon 12). The patient was treated successfully with fresh frozen plasma (FFP) infusions and maintained on prophylactic plasma therapy every 2-3 weeks, with reduced volume to minimize transfusion-related complications. Conclusion: This case underscores the importance of considering cTTP in unexplained recurrent thrombocytopenia and anemia, especially in cases with neurological involvement. Early diagnosis with ADAMTS13 activity testing and genetic confirmation is crucial to prevent life-threatening complications and optimize long-term management.

Large Language Models (LLMs) have revolutionized artificial intelligence applications, ranging from content generation to complex problem-solving. However, their performance, efficiency, and inherent biases vary significantly. This paper presents a comparative analysis of DeepSeek R1, ChatGPT, Gemini, Alibaba, and LLaMA, evaluating their reasoning capabilities, computational efficiency, and training costs. A key aspect of this study is an indepth examination of political bias, assessing how these models respond to politically sensitive topics. Using benchmarking datasets and controlled experiments, we analyze their Chain of Thought (CoT) reasoning, bias patterns, and censorship tendencies. The findings highlight crucial differences in AI governance, transparency, and the ethical implications of biased AI-generated content. Graphical insights and real-world examples further illustrate the impact of bias on AI-generated responses, offering recommendations for developing more transparent and fair AI models

Doppler frequency offset, Doppler spreading, and multipath effects are induced by the rapid movement of Low Earth Orbit (LEO) satellites, which collectively result in two-dimensional (2D) time-frequency fading within Non-Terrestrial Network (NTN) systems. Consequently, this leads to a degradation in the signal-to-noise ratio (SNR) uniformity and deep fading across the time-frequency grid in Orthogonal Frequency Division Multiplexing (OFDM) systems, which significantly impairs the bit error rate (BER) performance. The Orthogonal Time Frequency Space (OTFS) scheme is capable of addressing 2D time-frequency fading but at the cost of increasing the complexity of the receiver. In this work, an orthogonal transform-assisted OFDM (OTA-OFDM) scheme is proposed, which is based on orthogonal transforms to map data symbols into the time-frequency grid, effectively spreading the data symbol energy throughout the time-frequency domain. Simulations within a 400 MHz NTN system indicate that at a BER of 10-3, OTA-OFDM outperforms OFDM with SNR gains of 3.73 dB and 1.92 dB in NTN-TDL-B and NTN-TDL-D channels under QPSK modulation. It also obtains 3.24 dB and 1.54 dB SNR gain respectively under 16-QAM modulation. In addition, OTA-OFDM achieved an 93.33% reduction in receiver channel estimation and equalizer module complexity while matching the performance of OTFS.