bluuebunny/crossref_metadata_2025_split huggingface dataset:
Silencing hippocampal CA2 reduces behavioral flexibility in spatial learning
Authors: Lehr Andrew B. , Hitti Frederick L. , Deibel Scott H. , Stöber Tristan M. 
Published: March 2023

AbstractThe hippocampus is a key structure involved in learning and remembering spatial information. However, the extent to which hippocampal region CA2 is involved in these processes remains unclear. Here, we show that chronically silencing dorsal CA2 impairs reversal learning in the Morris water maze. After platform relocation, CA2‐silenced mice spent more time in the vicinity of the old platform location and less time in the new target quadrant. Accordingly, behavioral strategy analysis revealed increased perseverance in navigating to the old location during the first day and an increased use of non‐spatial strategies during the second day of reversal learning. Confirming previous indirect indications, these results demonstrate that CA2 is recruited when mice must flexibly adapt their behavior as task contingencies change. We discuss how these findings can be explained by recent theories of CA2 function and outline testable predictions to understand the underlying neural mechanisms. Demonstrating a direct involvement of CA2 in spatial learning, this work lends further support to the notion that CA2 plays a fundamental role in hippocampal information processing.
NMDA receptor activity during postnatal development determines intrinsic excitability and mossy fiber long‐term potentiation of CA3 pyramidal cells
Authors: Márquez Luis A. , Griego Ernesto , López Rubalcava Carolina , Galván Emilio J. 
Published: March 2023

AbstractExperimental manipulations that interfere with the functional expression of N‐methyl‐D‐aspartate receptors (NMDARs) during prenatal neurodevelopment or critical periods of postnatal development are models that mimic behavioral and neurophysiological abnormalities of schizophrenia. Blockade of NMDARs with MK‐801 during early postnatal development alters glutamate release and impairs the induction of NMDAR‐dependent long‐term plasticity at the CA1 area of the hippocampus. However, it remains unknown if other forms of hippocampal plasticity, such as α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid receptor (AMPAR)‐mediated short‐ and long‐term potentiation, are compromised in response to neonatal treatment with MK‐801. Consistent with this tenet, short‐ and long‐term potentiation between dentate gyrus axons, the mossy fibers (MF), onto CA3 pyramidal cells (CA3 PCs) are mediated by AMPARs. By combining whole‐cell patch clamp and extracellular recordings, we have demonstrated that transient blockade of NMDARs during early postnatal development induces a series of pre‐ and postsynaptic modifications at the MF—CA3 synapse. We found reduced glutamate release from the mossy boutons, increased paired‐pulse ratio, and reduced AMPAR‐mediated MF LTP levels. At the postsynaptic level, we found an altered NMDA/AMPA ratio and dysregulation of several potassium conductances that increased the excitability of CA3 PCs. In addition, MK‐801‐treated animals exhibited impaired spatial memory retrieval in the Barnes maze task. Our data demonstrate that transient hypofunction of NMDARs impacts NMDAR‐independent forms of synaptic plasticity of the hippocampus.
Noise response in monomolecular closed systems
Authors: Fajiculay Erickson , Hsu Chao‐Ping 
Published: March 2023

AbstractOne of the primary interests in understanding biological systems is the interaction between noise and cellular regulation. Noise levels can be altered by rate constant perturbations, which may result in an imbalance of important biological functions. Although the theory of noise localization can estimate noise perturbation response, it is currently limited to open systems, where the majority of biological networks belong. However, during their lifetime, some components of biological systems participate in reactions that can be categorized under a closed system. Therefore, a counterpart theory for closed systems is desirable. In this work, steady‐state perturbations of monomolecular closed systems and ways to estimate the response of noise as (co)variances are explored. We extend the structural sensitivity analysis for analyzing noise response patterns by using additional clues derived from multinomial assumptions. We identified scenarios in which this combination might fail in noise prediction, which we call noise flip, arising from the nonlinear dependence of variance upon composition. Nevertheless, theoretical intuition and simulation show that noise flip diminishes with increasing system size. This work provides an efficient and scalable means to estimate noise responses with potential applications in model discrimination, network‐wide response scanning, and reconstruction.
A laboratory model of canine search vigilance decrement, II: Noncontingent reward and Pavlovian appetitive stimuli
Authors: DeChant Mallory , Aviles Rosa Edgar O. , Prada‐Tiedemann Paola A. , Hall Nathaniel James 
Published: March 2023

AbstractDetection dogs have demonstrated reduced performance in operational settings when required to search in an environment where few to no target odors are present. This study's purpose was to increase detection dog accuracy using noncontingent reward (NCR) and Pavlovian stimuli associated with reward. Eighteen dogs were randomly spilt into two groups and received four 40‐trial sessions in an operational and training context at 90% odor prevalence (baseline). Following baseline, in the operational context (now at 10% odor prevalence), experimental dogs received an NCR schedule consisting of delivering food rewards at the end of 66% of trials. After the NCR Test, dogs returned to baseline. During baseline, the experimental dogs received 10 days of delayed Pavlovian conditioning to a tone. During the test phase, the conditioned stimulus (tone) was presented to experimental dogs on average every two trials for 30 s in the operational context (now at 10% odor prevalence). Overall, NCR showed a nonsignificant trend for increased responding in the experimental group but tended to increase false alerts; therefore, a permutation of an NCR‐like reward schedule may maintain search. The Pavlovian conditioned stimulus didn't decrease timeouts or improve accuracy, but a within‐session analysis indicated that the dogs were more likely to time out and less likely to false alert when the tone was on than when it was off.
Novel nutrition strategies to enhance recovery after surgery
Authors: Martindale Robert G. 
Published: March 2023

AbstractSurgery and traumatic injury set off a cascade of metabolic changes that are becoming better understood. Recently, strategies and protocols have been developed for optimizing outcomes, and this has yielded beneficial results. This brief review evaluates three specific nutrition or metabolic interventions in the postoperative setting that attempt to optimize outcomes. We limited this to three subspecialty areas including oncologic surgery, orthopedic surgery, and cardiac surgery. These agents included fish oils, factors to prevent dysbiosis, and resistance exercise and its role in enhancing protein update. Where these novel agents fit into the basic tenets of postoperative nutrition interventions does not change the narrative: deliver graduated early enteral feeding to attenuate the metabolic response to surgical stress, maintain the gastrointestinal mucosal barrier, use immune/metabolic modulation to enhance immune response while attenuating excessive inflammation, and support the microbiome.
THE IMPORTANCE OF BEING A DIVERSITY AND INCLUSION AMBASSADOR
Authors: Warren Celeste R. 
Published: March 2023

AbstractThe author, a longtime corporate executive, writes that “everyone must play a role in creating a diverse and inclusive work environment in any organization.” She notes that a “Diversity and Inclusion Ambassador is a person who acts as a representative or promoter of diversity and inclusion within the organization.” Her framework for becoming an ambassador is in three parts, which in her words are (1) Look at yourself. (2) Take an inventory of your surroundings. (3) Take action. In step one, “do a self‐reflection and assessment to determine what your strengths and areas of development are.” Step two involves “taking an inventory of your surroundings so you can know what to do to help others.” In step three, “you have to put into action the revelations you have after your initial assessments.” Ambassadors can be either individual contributors or C‐Suite leaders. Regarding the former, “For those employees who are not people managers, they are still instrumental to organizations creating a diverse and inclusive culture.” For the latter, “acting as a diversity and inclusion ambassador means that you are exemplifying the ideals of diversity and inclusion and promoting those ideals to others throughout your organization.” Examples are provided for how to make these roles effective for both contributors and leaders.
THE HUMAN SIDE OF INNOVATION
Authors: Porcini Mauro 
Published: March 2023

AbstractThe author discusses his journey from growing up in the north of Italy to his current role as the first‐ever Chief Design Officer of PepsiCo, the food and beverage multinational corporation. He describes what he calls his mission of human‐centered innovation. What is required, he notes, is people whom he dubs “the unicorns.” He writes that “at PepsiCo, we have an organization of more than 300 design and innovation experts spread across fifteen locations in every region of the world with a full diversity of technical skills and personal backgrounds. Our innovation team has gained more than 1,800 awards and recognitions in less than ten years.” He stresses the importance of kindness in these unicorns, and that they “possess humanity, generosity, and sensitivity. They are transparent, sincere, and inspire trust.” Within himself, he cultivates an “insatiable curiosity for everything around me. Curiosity is a portal to access knowledge and an instigator for inspiration.” He says that society, especially through education systems, should help people develop the qualities of unicorns early in life. “I believe that,” he writes, “aside from teaching math, literature, geography, philosophy, and finance, schools everywhere should educate people on the qualities of the unicorns.”
Resolvent family for the evolution process with memory
Authors: Xu Gen Qi 
Published: March 2023

AbstractIn this paper, we investigate a class of the linear evolution process with memory in Banach space by a different approach. Suppose that the linear evolution process is well posed, we introduce a family pair of bounded linear operators, , that is, called the resolvent family for the linear evolution process with memory, the is called the memory effect family. In this paper, we prove that the families and are exponentially bounded, and the family associate with an operator pair that is called generator of the resolvent family. Using , we derive associated differential equation with memory and representation of via L. These results give necessary conditions of the well‐posed linear evolution process with memory. To apply the resolvent family to differential equation with memory, we present a generation theorem of the resolvent family under some restrictions on . The obtained results can be directly applied to linear delay differential equation, integro‐differential equation and functional differential equations.
Report on the AAPM deep‐learning spectral CT Grand Challenge
Authors: Sidky Emil Y. , Pan Xiaochuan 
Published: March 2023

AbstractBackgroundThis Special Report summarizes the 2022 AAPM Grand Challenge on Deep‐Learning spectral Computed Tomography (DL‐spectral CT) image reconstruction.PurposeThe purpose of the challenge is to develop the most accurate image reconstruction algorithm possible for solving the inverse problem associated with a fast kilovolt switching dual‐energy CT scan using a three tissue‐map decomposition. Participants could choose to use a deep‐learning (DL), iterative, or a hybrid approach.MethodsThe challenge is based on a 2D breast CT simulation, where the simulated breast phantom consists of three tissue maps: adipose, fibroglandular, and calcification distributions. The phantom specification is stochastic so that multiple realizations can be generated for DL approaches. A dual‐energy scan is simulated where the x‐ray source potential of successive views alternates between 50 and 80 kilovolts (kV). A total of 512 views are generated, yielding 256 views for each source voltage. We generate 50 and 80 kV images by use of filtered back‐projection (FBP) on negative logarithm processed transmission data. For participants who develop a DL approach, 1000 cases are available. Each case consists of the three 512 × 512 tissue maps, 50 and 80‐kV transmission data sets and their corresponding FBP images. The goal of the DL network would then be to predict the material maps from either the transmission data, FBP images, or a combination of the two. For participants developing a physics‐based approach, all of the required modeling parameters are made available: geometry, spectra, and tissue attenuation curves. The provided information also allows for hybrid approaches where physics is exploited as well as information about the scanned object derived from the 1000 training cases. Final testing is performed by computation of root‐mean‐square error (RMSE) for predictions on the tissue maps from 100 new cases.ResultsTest phase submission were received from 18 research groups. Of the 18 submissions, 17 were results obtained with algorithms that involved DL. Only the second place finishing team developed a physics‐based image reconstruction algorithm. Both the winning and second place teams had highly accurate results where the RMSE was nearly zero to single floating point precision. Results from the top 10 also achieved a high degree of accuracy; and as a result, this special report outlines the methodology developed by each of these groups.ConclusionsThe DL‐spectral CT challenge successfully established a forum for developing image reconstruction algorithms that address an important inverse problem relevant for spectral CT.
Modeling the impact of tissue oxygen profiles and oxygen depletion parameter uncertainties on biological response and therapeutic benefit of FLASH
Authors: Zhu Hongyu , Schuemann Jan , Zhang Qixian , Gerweck Leo E. 
Published: March 2023

AbstractBackgroundUltra‐high dose rate (FLASH) radiation has been reported to efficiently suppress tumor growth while sparing normal tissue; however, the mechanism of the differential tissue sparing effect is still not known. Oxygen has long been known to profoundly impact radiobiological responses, and radiolytic oxygen depletion has been considered to be a possible cause or contributor to the FLASH phenomenon.PurposeThis work investigates the impact of tissue pO2 profiles, oxygen depletion per unit dose (g), and the oxygen concentration yielding half‐maximum radiosensitization (the average of its maximum value and one) (k) in tumor and normal tissue.MethodsWe developed a model that considers the dependent relationship between oxygen depletion and change of radiosensitivity by FLASH irradiation. The model assumed that FLASH irradiation depletes intracellular oxygen more rapidly than it diffuses into the cell from the extracellular environment. Cell survival was calculated based on the linear quadratic‐linear model and the radiosensitivity related parameters were adjusted in 1 Gy increments of the administered dose. The model reproduced published experimental data that were obtained with different cell lines and oxygen concentrations, and was used to analyze the impact of parameter uncertainties on the radiobiological responses. This study expands the oxygen depletion analysis of FLASH to normal human tissue and tumor based on clinically determined aggregate and individual patient pO2 profiles.ResultsThe results show that the pO2 profile is the most essential factor that affects biological response and analyses based on the median pO2 rather than the full pO2 profile can be unreliable and misleading. Additionally, the presence of a small fraction of cells on the threshold of radiobiologic hypoxia substantially alters biological response due to FLASH oxygen depletion. We found that an increment in the k value is generally more protective of tumor than normal tissue due to a higher frequency of lower pO2 values in tumors. Variation in the g value affects the dose at which oxygen depletion impacts response, but does not alter the dose‐dependent response trends, if the g value is identical in both tumor and normal tissue.ConclusionsThe therapeutic efficacy of FLASH oxygen depletion is likely patient and tissue‐dependent. For breast cancer, FLASH is beneficial in a minority of cases; however, in a subset of well oxygenated tumors, a therapeutic gain may be realized due to induced normal tissue hypoxia.
Prostate cancer segmentation from MRI by a multistream fusion encoder
Authors: Jiang Mingjie , Yuan Baohua , Kou Weixuan , Yan Wen , Marshall Harry , Yang Qianye , Syer Tom , Punwani Shonit , Emberton Mark , Barratt Dean C. , Cho Carmen C. M. , Hu Yipeng , Chiu Bernard 
Published: March 2023

AbstractBackgroundTargeted prostate biopsy guided by multiparametric magnetic resonance imaging (mpMRI) detects more clinically significant lesions than conventional systemic biopsy. Lesion segmentation is required for planning MRI‐targeted biopsies. The requirement for integrating image features available in T2‐weighted and diffusion‐weighted images poses a challenge in prostate lesion segmentation from mpMRI.PurposeA flexible and efficient multistream fusion encoder is proposed in this work to facilitate the multiscale fusion of features from multiple imaging streams. A patch‐based loss function is introduced to improve the accuracy in segmenting small lesions.MethodsThe proposed multistream encoder fuses features extracted in the three imaging streams at each layer of the network, thereby allowing improved feature maps to propagate downstream and benefit segmentation performance. The fusion is achieved through a spatial attention map generated by optimally weighting the contribution of the convolution outputs from each stream. This design provides flexibility for the network to highlight image modalities according to their relative influence on the segmentation performance. The encoder also performs multiscale integration by highlighting the input feature maps (low‐level features) with the spatial attention maps generated from convolution outputs (high‐level features). The Dice similarity coefficient (DSC), serving as a cost function, is less sensitive to incorrect segmentation for small lesions. We address this issue by introducing a patch‐based loss function that provides an average of the DSCs obtained from local image patches. This local average DSC is equally sensitive to large and small lesions, as the patch‐based DSCs associated with small and large lesions have equal weights in this average DSC.ResultsThe framework was evaluated in 931 sets of images acquired in several clinical studies at two centers in Hong Kong and the United Kingdom. In particular, the training, validation, and test sets contain 615, 144, and 172 sets of images, respectively. The proposed framework outperformed single‐stream networks and three recently proposed multistream networks, attaining F1 scores of 82.2 and 87.6% in the lesion and patient levels, respectively. The average inference time for an axial image was 11.8 ms.ConclusionThe accuracy and efficiency afforded by the proposed framework would accelerate the MRI interpretation workflow of MRI‐targeted biopsy and focal therapies.
Deep learning‐based fast volumetric imaging using kV and MV projection images for lung cancer radiotherapy: A feasibility study
Authors: Lei Yang , Tian Zhen , Wang Tonghe , Roper Justin , Xie Huiqiao , Kesarwala Aparna H. , Higgins Kristin , Bradley Jeffrey D. , Liu Tian , Yang Xiaofeng 
Published: March 2023

AbstractPurposeThe long acquisition time of CBCT discourages repeat verification imaging, therefore increasing treatment uncertainty. In this study, we present a fast volumetric imaging method for lung cancer radiation therapy using an orthogonal 2D kV/MV image pair.MethodsThe proposed model is a combination of 2D and 3D networks. The proposed model consists of five major parts: (1) kV and MV feature extractors are used to extract deep features from the perpendicular kV and MV projections. (2) The feature‐matching step is used to re‐align the feature maps to their projection angle in a Cartesian coordinate system. By using a residual module, the feature map can focus more on the difference between the estimated and ground truth images. (3) In addition, the feature map is downsized to include more global semantic information for the 3D estimation, which is useful to reduce inhomogeneity. By using convolution‐based reweighting, the model is able to further increase the uniformity of image. (4) To reduce the blurry noise of generated 3D volume, the Laplacian latent space loss calculated via the feature map that is extracted via specifically‐learned Gaussian kernel is used to supervise the network. (5) Finally, the 3D volume is derived from the trained model. We conducted a proof‐of‐concept study using 50 patients with lung cancer. An orthogonal kV/MV pair was generated by ray tracing through CT of each phase in a 4D CT scan. Orthogonal kV/MV pairs from nine respiratory phases were used to train this patient‐specific model while the kV/MV pair of the remaining phase was held for model testing.ResultsThe results are based on simulation data and phantom results from a real Linac system. The mean absolute error (MAE) values achieved by our method were 57.5 HU and 77.4 HU within body and tumor region‐of‐interest (ROI), respectively. The mean achieved peak‐signal‐to‐noise ratios (PSNR) were 27.6 dB and 19.2 dB within the body and tumor ROI, respectively. The achieved mean normalized cross correlation (NCC) values were 0.97 and 0.94 within the body and tumor ROI, respectively. A phantom study demonstrated that the proposed method can accurately re‐position the phantom after shift. It is also shown that the proposed method using both kV and MV is superior to current method using kV or MV only in image quality.ConclusionThese results demonstrate the feasibility and accuracy of our proposed fast volumetric imaging method from an orthogonal kV/MV pair, which provides a potential solution for daily treatment setup and verification of patients receiving radiation therapy for lung cancer.