Stereotactic central/core ablative radiation therapy: results of a phase I study of a novel strategy to treat bulky tumor.

Purpose: Bulky tumor remains as a challenge to surgery, chemotherapy and conventional radiation therapy. Hence, in efforts to overcome this challenge, we designed a novel therapeutic paradigm via strategy of Stereotactic Central/Core Ablative Radiation Therapy (SCART).), which is based on the principles of SBRT (stereotactic body radiation therapy and spatially fractionated radiation therapy (SFRT). We intend to safely deliver an ablative dose to the core of the tumor and with a low dose at tumor edge. The purpose of the phase 1 study was to determine dose-limiting toxicities (DLT)s and the Maximum Tolerated Dose (MTD) of SCART. Methods and materials: We defined a SCART-plan volume inside the tumor, which is proportional to the dimension of tumor. VMAT/Cyberknife technique was adopted. In the current clinical trial; Patients with biopsy proven recurrent or metastatic bulky cancers were enrolled. The five dose levels were 15 Gy X1, 15Gy X3, 18GyX3, 21GyX3 and 24GyX3, while keeping the whole tumor GTV's border dose at 5Gy each fraction. There was no restriction on concurrent systemic chemotherapy agents. Results: 21 patients were enrolled and underwent SCART. All 21 patients have eligible data for study follow-up. Radiotherapy was well tolerated with all treatment completed as scheduled. The dose was escalated for two patients to 24GyX3. No grade 3 or higher toxicity was observed in any of the enrolled patients. The average age of patients was 66 years (range: 14-85) and 13 (62%) patients were male. The median SCART dose was 18Gy (range: 15 - 24). Six out of the 18 patients with data for overall survival (OS) died, and the median time to death was 16.3 months (range: 1 - 25.6). The mean percent change for tumor shrinkage between first visit volumes and post-SCART volumes was 49.5% (SD: 40.89, p-value:0.009). Conclusion: SCART was safely escalated to 24 GyX 3 fractions, which is the maximum Tolerated Dose (MTD) for SCART. This regimen will be used in future phase II trials.

Which Modality of SFRT Should be Considered First for Bulky Tumor Radiation Therapy, GRID or LATTICE?

Spatially fractionated radiation therapy (SFRT), also known as the GRID and LATTICE radiotherapy (GRT, LRT), the concept of treating tumors by delivering a spatially modulated dose with highly non-uniform dose distributions, is a treatment modality of growing interest in radiation oncology, physics, and radiation biology. Clinical experience in SFRT has suggested that GRID and LATTICE therapy can achieve a high response and low toxicity in the treatment of refractory and bulky tumors. Limited initially to GRID therapy using block collimators, advanced, and versatile multi-leaf collimators, volumetric modulated arc technologies and particle therapy have since increased the capabilities and individualization of SFRT and expanded the clinical investigation of SFRT to various dosing regimens, multiple malignancies, tumor types and sites. As a 3D modulation approach outgrown from traditional 2D GRID, LATTICE therapy aims to reconfigure the traditional SFRT as spatial modulation of the radiation is confined solely to the tumor volume. The distinctively different beam geometries used in LATTICE therapy have led to appreciable variations in dose-volume distributions, compared to GRID therapy. The clinical relevance of the variations in dose-volume distribution between LATTICE and traditional GRID therapies is a crucial factor in determining their adoption in clinical practice. In this Point-Counterpoint contribution, the authors debate the pros and cons of GRID and LATTICE therapy. Both modalities have been used in clinics and their applicability and optimal use have been discussed in this article.

Optimizing GRID and Lattice Spatially Fractionated Radiation Therapy: Innovative Strategies for Radioresistant and Bulky Tumor Management.

Treating radioresistant and bulky tumors is challenging due to their inherent resistance to standard therapies and their large size. GRID and lattice spatially fractionated radiation therapy (simply referred to GRID RT and LRT) offer promising techniques to tackle these issues. Both approaches deliver radiation in a grid-like or lattice pattern, creating high-dose peaks surrounded by low-dose valleys. This pattern enables the destruction of significant portions of the tumor while sparing healthy tissue. GRID RT uses a 2-dimensional pattern of high-dose peaks (15-20 Gy), while LRT delivers a three-dimensional array of high-dose vertices (10-20 Gy) spaced 2-5 cm apart. These techniques are beneficial for treating a variety of cancers, including soft tissue sarcomas, osteosarcomas, renal cell carcinoma, melanoma, gastrointestinal stromal tumors (GISTs), pancreatic cancer, glioblastoma, and hepatocellular carcinoma. The specific grid and lattice patterns must be carefully tailored for each cancer type to maximize the peak-to-valley dose ratio while protecting critical organs and minimizing collateral damage. For gynecologic cancers, the treatment plan should align with the international consensus guidelines, incorporating concurrent chemotherapy for optimal outcomes. Despite the challenges of precise dosimetry and patient selection, GRID RT and LRT can be cost-effective using existing radiation equipment, including particle therapy systems, to deliver targeted high-dose radiation peaks. This phased approach of partial high-dose induction radiation therapy with standard fractionated radiation therapy maximizes immune modulation and tumor control while reducing toxicity. Comprehensive treatment plans using these advanced techniques offer a valuable framework for radiation oncologists, ensuring safe and effective delivery of therapy for radioresistant and bulky tumors. Further clinical trials data and standardized guidelines will refine these strategies, helping expand access to innovative cancer treatments.

Ag-Incorporated Cr-Doped BaTiO3 Aerogel toward Enhanced Photocatalytic Degradation of Methyl Orange.

A novel Cr-doped BaTiO3 aerogel was successfully synthesized using a co-gelation technique that involves two metallic alkoxides and a supercritical drying method. This freshly prepared aerogel has a high specific surface area of over 100 m2/g and exhibits improved responsiveness to the simulated sunlight spectrum. Methyl orange (MO) was chosen as the simulated pollutant, and the results reveal that the Cr-doped BaTiO3 aerogel, when modified with the noble metal silver (Ag), achieves a pollutant removal rate approximately 3.2 times higher than that of the commercially available P25, reaching up to 92% within 60 min. The excellent photocatalytic performance of the Ag-modified Cr-doped BaTiO3 aerogel can be primarily attributed to its extensive specific surface area and three-dimensional porous architecture. Furthermore, the incorporation of Ag nanoparticles effectively suppresses the recombination of photo-generated electrons and holes. Stability and reusability tests have confirmed the reliability of the Ag-modified Cr-doped BaTiO3 aerogel. Therefore, this material emerges as a highly promising candidate for the treatment of textile wastewater.

Impact on sulfadiazine bio-accessibility in soils through organic diffusive gradients in thin films (o-DGT): Differentiation based on microplastic polymers, aging, and soil properties.

Due to the similar sources of swage irrigation, organic fertilizer, and sludge application, microplastics (MPs) and antibiotics coexist inevitably in the agriculture soils. However, the impacts of MPs with different polymer types and aging status on the bio-accessibility of co-existing antibiotics in soils remained unclear. Therefore, we using the diffusive gradients films for organic compounds devices (o-DGT) to evaluated the distribution of sulfadiazine (SDZ) in both paddy soil and saline soil amended with 0.5 % (w/w) MPs. Four polymer types (polyethylene: PE, polypropylene: PP, polyamide: PA, and polyethylene terephthalate: PET) and two aging statuses (aged PE and aged PP) of MPs were used in this study. Results showed that soil properties significantly influence the partition of SDZ in soil and soil solution, and SDZ gained a lower degradation rate but higher mobility in saline soil. MPs pose different impacts on partition of SDZ between paddy soil and saline soil. Notably, PP reduced the labile solid phase-solution phase partition coefficient (Kdl) by 17.7 % in paddy soil, while PE, PP, and aPE increased the Kdl value by 2.00, 1.62, and 2.81 times in saline soil. Besides, in saline soil, all the MPs reduced the SDZ concentration in the soil solution, while significantly increased the SDZ in o-DGT phase. Conversely, MPs did not impact the SDZ's o-DGT concentration in paddy soil. Additionally, MPs increased the R value of SDZ in two soils, especially in saline soil. It suggested that MPs could potentially enhance the resupply of SDZ from soil to plants, particularly under saline conditions. Furthermore, aged MPs had a more pronounced effect on these indicators compared to virgin MPs in saline soil. Therefore, MPs in soil poses a potential risk for biota's uptake of SDZ, particularly in fragile environment. Moreover, the risk intensifies with aged MPs.

Assessing eco-geographic influences on COVID-19 transmission: a global analysis.

COVID-19 has been massively transmitted for almost 3 years, and its multiple variants have caused serious health problems and an economic crisis. Our goal was to identify the influencing factors that reduce the threshold of disease transmission and to analyze the epidemiological patterns of COVID-19. This study served as an early assessment of the epidemiological characteristics of COVID-19 using the MaxEnt species distribution algorithm using the maximum entropy model. The transmission of COVID-19 was evaluated based on human factors and environmental variables, including climate, terrain and vegetation, along with COVID-19 daily confirmed case location data. The results of the SDM model indicate that population density was the major factor influencing the spread of COVID-19. Altitude, land cover and climatic factor showed low impact. We identified a set of practical, high-resolution, multi-factor-based maximum entropy ecological niche risk prediction systems to assess the transmission risk of the COVID-19 epidemic globally. This study provided a comprehensive analysis of various factors influencing the transmission of COVID-19, incorporating both human and environmental variables. These findings emphasize the role of different types of influencing variables in disease transmission, which could have implications for global health regulations and preparedness strategies for future outbreaks.

Distinct neural activities of the cortical layer 2/3 across isoflurane anesthesia: A large-scale simultaneous observation of neurons.

Anesthesia inhibits neural activity in the brain, causing patients to lose consciousness and sensation during the surgery. Layers 2/3 of the cortex are important structures for the integration of information and consciousness, which are closely related to normal cognitive function. However, the dynamics of the large-scale population of neurons across multiple regions in layer 2/3 during anesthesia and recovery processes remains unclear. We conducted simultaneous observations and analysis of large-scale calcium signaling dynamics across multiple cortical regions within cortical layer 2/3 during isoflurane anesthesia and recovery in vivo by high-resolution wide-field microscopy. Under isoflurane-induced anesthesia, there is an overall decrease in neuronal activity across multiple regions in the cortical layer 2/3. Notably, some neurons display a paradoxical increase in activity during anesthesia. Additionally, the activity among multiple cortical regions under anesthesia was homogeneous. It is only during the recovery phase that variability emerges in the extent of increased neural activity across different cortical regions. Within the same duration of anesthesia, neural activity did not return to preanesthetic levels. To sum up, anesthesia as a dynamic alteration of brain functional networks, encompassing shifts in patterns of neural activity, homogeneousness among cortical neurons and regions, and changes in functional connectivity. Recovery from anesthesia does not entail a reversal of these effects within the same timeframe.

Development and validation of a nomogram to predict postoperative delirium in older patients after major abdominal surgery: a retrospective case-control study.

BACKGROUND: Postoperative delirium is a common complication in older patients, with poor long-term outcomes. This study aimed to investigate risk factors and develop a predictive model for postoperative delirium in older patients after major abdominal surgery. METHODS: This study retrospectively recruited 7577 patients aged ≥ 65 years who underwent major abdominal surgery between January 2014 and December 2018 in a single hospital in Beijing, China. Patients were divided into a training cohort (n = 5303) and a validation cohort (n = 2224) for univariate and multivariate logistic regression analyses and to build a nomogram. Data were collected for 43 perioperative variables, including demographics, medical history, preoperative laboratory results, imaging, and anesthesia information. RESULTS: Age, chronic obstructive pulmonary disease, white blood cell count, glucose, total protein, creatinine, emergency surgery, and anesthesia time were associated with postoperative delirium in multivariate analysis. We developed a nomogram based on the above 8 variables. The nomogram achieved areas under the curve of 0.731 and 0.735 for the training and validation cohorts, respectively. The discriminatory ability of the nomogram was further assessed by dividing the cases into three risk groups (low-risk, nomogram score < 175; medium-risk, nomogram score 175~199; high-risk, nomogram score > 199; P < 0.001). Decision curve analysis revealed that the nomogram provided a good net clinical benefit. CONCLUSIONS: We developed a nomogram that could predict postoperative delirium with high accuracy and stability in older patients after major abdominal surgery.

Analysis the molecular similarity of least common amino acid sites in ACE2 receptor to predict the potential susceptible species for SARS-CoV-2.

SARS-CoV-2 infections in animals have been reported globally. However, the understanding of the complete spectrum of animals susceptible to SARS-CoV-2 remains limited. The virus's dynamic nature and its potential to infect a wide range of animals are crucial considerations for a One Health approach that integrates both human and animal health. This study introduces a bioinformatic approach to predict potential susceptibility to SARS-CoV-2 in both domestic and wild animals. By examining genomic sequencing, we establish phylogenetic relationships between the virus and its potential hosts. We focus on the interaction between the SARS-CoV-2 genome sequence and specific regions of the host species' ACE2 receptor. We analyzed and compared ACE2 receptor sequences from 29 species known to be infected, selecting 10 least common amino acid sites (LCAS) from key binding domains based on similarity patterns. Our analysis included 49 species across primates, carnivores, rodents, and artiodactyls, revealing complete consistency in the LCAS and identifying them as potentially susceptible. We employed the LCAS similarity pattern to predict the likelihood of SARS-CoV-2 infection in unexamined species. This method serves as a valuable screening tool for assessing infection risks in domestic and wild animals, aiding in the prevention of disease outbreaks.

Spatial distribution, source, and fate of per- and polyfluoroalkyl substances in the surrounding environment of closed and converted fluorochemical factories in Fujian, China.

Following the closure of perfluorooctanesulfonic acid (PFOS) production to comply with the Stockholm Convention regulations or restrictions, manufacturers have shifted to developing short-chain alternatives like perfluorobutane sulfonic acid (PFBS). However, limited research has been conducted to evaluate the impact of this transition on the surrounding environment. This study focused on the spatial distribution, source, and fate of 18 per- and polyfluoroalkyl substances (PFAS) in the surrounding environment of the closure and transformation of two PFAS manufacturing plants in Fujian, China. The total concentrations of PFAS in surface water, sediment, and fish were within the range of 48.9-72,400 ng/L, 0.930-57.6 ng/g dw, and 3.33-1245 ng/g dw, respectively. The predominant compounds were PFBS, PFOS, and perfluorooctanoic acid (PFOA) among the three matrices. Principal component analysis highlighted significant differences in PFAS profiles across different regions of the Futun River, suggesting diverse sources of PFAS. Source apportionment indicated that despite being closed or converted for almost three years, the two factories still significantly impacted the surrounding environment. The shutdown factory mainly released PFAS characterized by perfluoroalkyl sulfonic acids. In contrast, the PFAS were released from conversion plant with the fingerprint being PFBS and perfluoroalkyl carboxylic acids. The conversion of the factories has resulted in the coexistence of long-chain and short-chain PFAS, which has complicated the composition of PFAS in the environment. As sewage treatment plant could not effectively remove PFBS and perfluorobutanoic acid (PFBA) in wastewater, and due to their strong migration ability, these chemicals had a wider impact range, increasing the difficulty of environmental restoration and management. Risk assessment showed that PFAS downstream of the two factories posed high or moderate ecological risks. Specifically, PFBS, PFOS, and PFOA displayed the highest risk quotients and should be paid further attention.

Isolation and Identification of Salinity-Tolerant Rhizobia and Nodulation Phenotype Analysis in Different Soybean Germplasms.

Increasing the soybean-planting area and increasing the soybean yield per unit area are two effective solutions to improve the overall soybean yield. Northeast China has a large saline soil area, and if soybeans could be grown there with the help of isolated saline-tolerant rhizobia, the soybean cultivation area in China could be effectively expanded. In this study, soybeans were planted in soils at different latitudes in China, and four strains of rhizobia were isolated and identified from the soybean nodules. According to the latitudes of the soil-sampling sites from high to low, the four isolated strains were identified as HLNEAU1, HLNEAU2, HLNEAU3, and HLNEAU4. In this study, the isolated strains were identified for their resistances, and their acid and saline tolerances and nitrogen fixation capacities were preliminarily identified. Ten representative soybean germplasm resources in Northeast China were inoculated with these four strains, and the compatibilities of these four rhizobium strains with the soybean germplasm resources were analyzed. All four isolates were able to establish different extents of compatibility with 10 soybean resources. Hefeng 50 had good compatibility with the four isolated strains, while Suinong 14 showed the best compatibility with HLNEAU2. The isolated rhizobacteria could successfully establish symbiosis with the soybeans, but host specificity was also present. This study was a preliminary exploration of the use of salinity-tolerant rhizobacteria to help the soybean nitrogen fixation in saline soils in order to increase the soybean acreage, and it provides a valuable theoretical basis for the application of saline-tolerant rhizobia.

Deep learning from latent spatiotemporal information of the heart: Identifying advanced bioimaging markers from echocardiograms.

A key strength of echocardiography lies in its integration of comprehensive spatiotemporal cardiac imaging data in real-time, to aid frontline or bedside patient risk stratification and management. Nonetheless, its acquisition, processing, and interpretation are known to all be subject to heterogeneity from its reliance on manual and subjective human tracings, which challenges workflow and protocol standardization and final interpretation accuracy. In the era of advanced computational power, utilization of machine learning algorithms for big data analytics in echocardiography promises reduction in cost, cognitive errors, and intra- and inter-observer variability. Novel spatiotemporal deep learning (DL) models allow the integration of temporal arm information based on unlabeled pixel echocardiographic data for convolution of an adaptive semantic spatiotemporal calibration to construct personalized 4D heart meshes, assess global and regional cardiac function, detect early valve pathology, and differentiate uncommon cardiovascular disorders. Meanwhile, data visualization on spatiotemporal DL prediction models helps extract latent temporal imaging features to develop advanced imaging biomarkers in early disease stages and advance our understanding of pathophysiology to support the development of personalized prevention or treatment strategies. Since portable echocardiograms have been increasingly used as point-of-care imaging tools to aid rural care delivery, the application of these new spatiotemporal DL techniques show the potentials in streamlining echocardiographic acquisition, processing, and data analysis to improve workflow standardization and efficiencies, and provide risk stratification and decision supporting tools in real-time, to prompt the building of new imaging diagnostic networks to enhance rural healthcare engagement.

The Spatial Niche and Influencing Factors of Desert Rodents.

Resource partitioning may allow species coexistence. Sand dunes in the typical steppe of Alxa Desert Inner Mongolia, China, consisting of desert, shrub, and grass habitats, provide an appropriate system for studies of spatial niche partitioning among small mammals. In this study, the spatial niche characteristics of four rodents, Orientallactaga sibirica, Meriones meridianus, Dipus sagitta, and Phodopus roborovskii, and their responses to environmental changes in the Alxa Desert were studied from 2017 to 2021. Using the capture-mark-recapture method, we tested if desert rodents with different biological characteristics and life history strategies under heterogeneous environmental conditions allocate resources in spatial niches to achieve sympatric coexistence. We investigated the influence of environmental factors on the spatial niche breadth of rodents using random forest and redundancy analyses. We observed that the spatial niche overlap between O. sibirica and other rodents is extremely low (overlap index ≤ 0.14). P. roborovskii had the smallest spatial niche breadth. Spatial niche overlap was observed in two distinct species pairs, M. meridianus and D. sagitta, and P. roborovskii and D. sagitta. The Pielou evenness index of rodent communities is closely related to the spatial distribution of rodents, and the concealment of habitats is a key factor affecting the spatial occupation of rodents.

Deep learning from atrioventricular plane displacement in patients with Takotsubo syndrome: lighting up the black-box.

Aims: The spatiotemporal deep convolutional neural network (DCNN) helps reduce echocardiographic readers' erroneous 'judgement calls' on Takotsubo syndrome (TTS). The aim of this study was to improve the interpretability of the spatiotemporal DCNN to discover latent imaging features associated with causative TTS pathophysiology. Methods and results: We applied gradient-weighted class activation mapping analysis to visualize an established spatiotemporal DCNN based on the echocardiographic videos to differentiate TTS (150 patients) from anterior wall ST-segment elevation myocardial infarction (STEMI, 150 patients). Forty-eight human expert readers interpreted the same echocardiographic videos and prioritized the regions of interest on myocardium for the differentiation. Based on visualization results, we completed optical flow measurement, myocardial strain, and Doppler/tissue Doppler echocardiography studies to investigate regional myocardial temporal dynamics and diastology. While human readers' visualization predominantly focused on the apex of the heart in TTS patients, the DCNN temporal arm's saliency visualization was attentive on the base of the heart, particularly at the atrioventricular (AV) plane. Compared with STEMI patients, TTS patients consistently showed weaker peak longitudinal displacement (in pixels) in the basal inferoseptal (systolic: 2.15 ± 1.41 vs. 3.10 ± 1.66, P < 0.001; diastolic: 2.36 ± 1.71 vs. 2.97 ± 1.69, P = 0.004) and basal anterolateral (systolic: 2.70 ± 1.96 vs. 3.44 ± 2.13, P = 0.003; diastolic: 2.73 ± 1.70 vs. 3.45 ± 2.20, P = 0.002) segments, and worse longitudinal myocardial strain in the basal inferoseptal (-8.5 ± 3.8% vs. -9.9 ± 4.1%, P = 0.013) and basal anterolateral (-8.6 ± 4.2% vs. -10.4 ± 4.1%, P = 0.006) segments. Meanwhile, TTS patients showed worse diastolic mechanics than STEMI patients (E'/septal: 5.1 ± 1.2 cm/s vs. 6.3 ± 1.5 cm/s, P < 0.001; S'/septal: 5.8 ± 1.3 cm/s vs. 6.8 ± 1.4 cm/s, P < 0.001; E'/lateral: 6.0 ± 1.4 cm/s vs. 7.9 ± 1.6 cm/s, P < 0.001; S'/lateral: 6.3 ± 1.4 cm/s vs. 7.3 ± 1.5 cm/s, P < 0.001; E/E': 15.5 ± 5.6 vs. 12.5 ± 3.5, P < 0.001). Conclusion: The spatiotemporal DCNN saliency visualization helps identify the pattern of myocardial temporal dynamics and navigates the quantification of regional myocardial mechanics. Reduced AV plane displacement in TTS patients likely correlates with impaired diastolic mechanics.

Diagnostic strategy of metagenomic next-generation sequencing for gram negative bacteria in respiratory infections.

OBJECTIVE: This study aims to identify the most effective diagnostic method for distinguishing pathogenic and non-pathogenic Gram-negative bacteria (GNB) in suspected pneumonia cases using metagenomic next-generation sequencing (mNGS) on bronchoalveolar lavage fluid (BALF) samples. METHODS: The effectiveness of mNGS was assessed on BALF samples collected from 583 patients, and the results were compared with those from microbiological culture and final clinical diagnosis. Three interpretational approaches were evaluated for diagnostic accuracy. RESULTS: mNGS outperformed culture significantly. Among the interpretational approaches, Clinical Interpretation (CI) demonstrated the best diagnostic performance with a sensitivity of 87.3%, specificity of 100%, positive predictive value of 100%, and negative predictive value of 98.3%. CI's specificity was significantly higher than Simple Interpretation (SI) at 37.9%. Additionally, CI excluded some microorganisms identified as putative pathogens by SI, including Haemophilus parainfluenzae, Haemophilus parahaemolyticus, and Klebsiella aerogenes. CONCLUSION: Proper interpretation of mNGS data is crucial for accurately diagnosing respiratory infections caused by GNB. CI is recommended for this purpose.

Regulating Cholesterol in Tumorigenesis: A Novel Paradigm for Tumor Nanotherapeutics.

During the past decade, "membrane lipid therapy", which involves the regulation of the structure and function of tumor cell plasma membranes, has emerged as a new strategy for cancer treatment. Cholesterol is an important component of the tumor plasma membrane and serves an essential role in tumor initiation and progression. This review elucidates the role of cholesterol in tumorigenesis (including tumor cell proliferation, invasion/metastasis, drug resistance, and immunosuppressive microenvironment) and elaborates on the potential therapeutic targets for tumor treatment by regulating cholesterol. More meaningfully, this review provides an overview of cholesterol-integrated membrane lipid nanotherapeutics for cancer therapy through cholesterol regulation. These strategies include cholesterol biosynthesis interference, cholesterol uptake disruption, cholesterol metabolism regulation, cholesterol depletion, and cholesterol-based combination treatments. In summary, this review demonstrates the tumor nanotherapeutics based on cholesterol regulation, which will provide a reference for the further development of "membrane lipid therapy" for tumors.

Practice Patterns of Spatially Fractionated Radiation Therapy: A Clinical Practice Survey.

Purpose: Spatially fractionated radiation therapy (SFRT) is increasingly used for bulky advanced tumors, but specifics of clinical SFRT practice remain elusive. This study aimed to determine practice patterns of GRID and Lattice radiation therapy (LRT)-based SFRT. Methods and Materials: A survey was designed to identify radiation oncologists' practice patterns of patient selection for SFRT, dosing/planning, dosimetric parameter use, SFRT platforms/techniques, combinations of SFRT with conventional external beam radiation therapy (cERT) and multimodality therapies, and physicists' technical implementation, delivery, and quality procedures. Data were summarized using descriptive statistics. Group comparisons were analyzed with permutation tests. Results: The majority of practicing radiation oncologists (United States, 100%; global, 72.7%) considered SFRT an accepted standard-of-care radiation therapy option for bulky/advanced tumors. Treatment of metastases/recurrences and nonmetastatic primary tumors, predominantly head and neck, lung cancer and sarcoma, was commonly practiced. In palliative SFRT, regimens of 15 to 18 Gy/1 fraction predominated (51.3%), and in curative-intent treatment of nonmetastatic tumors, 15 Gy/1 fraction (28.0%) and fractionated SFRT (24.0%) were most common. SFRT was combined with cERT commonly but not always in palliative (78.6%) and curative-intent (85.7%) treatment. SFRT-cERT time sequencing and cERT dose adjustments were variable. In curative-intent treatment, concurrent chemotherapy and immunotherapy were found acceptable by 54.5% and 28.6%, respectively. Use of SFRT dosimetric parameters was highly variable and differed between GRID and LRT. SFRT heterogeneity dosimetric parameters were more commonly used (P = .008) and more commonly thought to influence local control (peak dose, P = .008) in LRT than in GRID therapy. Conclusions: SFRT has already evolved as a clinical practice pattern for advanced/bulky tumors. Major treatment approaches are consistent and follow the literature, but SFRT-cERT combination/sequencing and clinical utilization of dosimetric parameters are variable. These areas may benefit from targeted education and standardization, and knowledge gaps may be filled by incorporating identified inconsistencies into future clinical research.

Would future climate warming cause zoonotic diseases to spread over long distances?

Dipus sagitta is a major rodent found in arid environments and desert areas. They feed on plant seeds, young branches and some small insects, and have hibernating habits. Peak Dipus sagitta numbers impact the construction of the plant community in the environment, but also have a human impact as these rodents carry a variety of parasitic fleas capable of spreading serious diseases to humans. Based on 216 present distribution records of Dipus sagitta and seven environmental variables, this article simulates the potential distribution of Dipus sagitta during the Last Glacial Maximum, the mid-Holocene, the present and the future (2070s, RCP4.5, RCP8.5). This study also analyzes the geographic changes of the population distribution and evaluates the importance of climate factors by integrating contribution rate, replacement importance value and the jackknife test using the MaxEnt model. In this study, we opted to assess the predictive capabilities of our model using the receiver operating characteristic (ROC) and partial receiver operating characteristic (pROC) metrics. The findings indicate that the AUC value exceeds 0.9 and the AUC ratio is greater than 1, indicating superior predictive performance by the model. The results showed that the main climatic factors affecting the distribution of the three-toed jerboa were precipitation in the coldest quarter, temperature seasonality (standard deviation), and mean annual temperature. Under the two warming scenarios of the mid-Holocene and the future, there were differences in the changes in the distribution area of the three-toed jerboa. During the mid-Holocene, the suitable distribution area of the three-toed jerboa expanded, with a 93.91% increase in the rate of change compared to the Last Glacial Maximum. The size of the three-toed jerboa's habitat decreases under both future climate scenarios. Compared to the current period, under the RCP4.5 emission scenario, the change rate is -2.96%, and under the RCP8.5 emission scenario, the change rate is -7.41%. This indicates a trend of contraction in the south and expansion in the north. It is important to assess changes in the geographic population of Dipus sagitta due to climate change to formulate population control strategies of these harmful rodents and to prevent and control the long-distance transmission of zoonotic diseases.

Gut microbiota and cognitive performance: A bidirectional two-sample Mendelian randomization.

PURPOSE: Previous studies have suggested a potential association between gut microbiota and neurological and psychiatric disorders. However, the causal relationship between gut microbiota and cognitive performance remains uncertain. METHODS: A two-sample Mendelian randomization (MR) study used SNPs linked to gut microbiota (n = 18,340) and cognitive performance (n = 257,841) from recent GWAS data. Inverse-variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode were employed. Heterogeneity was assessed via Cochran's Q test for IVW. Results were shown with funnel plots. Outliers were detected through leave-one-out method. MR-PRESSO and MR-Egger intercept tests were conducted to address horizontal pleiotropy influence. LIMITATIONS: Limited to European populations, generic level, and potential confounding factors. RESULTS: IVW analysis revealed detrimental effects on cognitive perfmance associated with the presence of genus Blautia (P = 0.013, 0.966[0.940-0.993]), Catenibacterium (P = 0.035, 0.977[0.956-0.998]), Oxalobacter (P = 0.043, 0.979[0.960-0.999]). Roseburia (P < 0.001, 0.935[0.906-0.965]), in particular, remained strongly negatively associated with cognitive performance after Bonferroni correction. Conversely, families including Bacteroidaceae (P = 0.043, 1.040[1.001-1.081]), Rikenellaceae (P = 0.047, 1.026[1.000-1.053]), along with genera including Paraprevotella (P = 0.044, 1.020[1.001-1.039]), Ruminococcus torques group (P = 0.016, 1.062[1.011-1.115]), Bacteroides (P = 0.043, 1.040[1.001-1.081]), Dialister (P = 0.027, 1.039[1.004-1.074]), Paraprevotella (P = 0.044, 1.020[1.001-1.039]) and Ruminococcaceae UCG003 (P = 0.007, 1.040[1.011-1.070]) had a protective effect on cognitive performance. CONCLUSIONS: Our results suggest that interventions targeting specific gut microbiota may offer a promising avenue for improving cognitive function in diseased populations. The practical application of these findings has the potential to enhance cognitive performance, thereby improving overall quality of life.