Auricular Acupressure in Relieving PONV and Promoting Gastrointestinal Function Recovery in Females After Laparoscopic Sleeve Gastrectomy: A Prospective Randomized Controlled Trial.

BACKGROUND: The role of current pharmacological treatment after laparoscopic sleeve gastrectomy (LSG) is limited. The incidence of postoperative nausea and vomiting (PONV) after LSG remains high. Auricular acupressure (AA) is believed to relieve PONV after laparoscopic surgeries, but its role in patients with obesity after LSG has yet to be confirmed. METHODS: Ninety-five female patients who underwent LSG were randomized into two groups: AA combined with conventional anti-nausea medication (AA group, 47 patients) or conventional anti-nausea medication group (control group, 48 patients). Index of nausea and vomiting and retching (INVR) scores, postoperative anti-vomiting medication use, time of first anus exhausting, time of first fluid intake, and time of first to get out of bed were collected within 48 h after surgery. RESULTS: Demographic data of patients in both groups were balanced and comparable. INVR score (F = 7.505, P = 0.007), vomiting score (F = 11.903, P = 0.001), and retching score (F = 12.098, P = 0.001) were significantly lower in the AA group than that in the control group within 48 h postoperatively. Use of metoclopramide was significantly less in the AA group than in the control group (4.7 [5.5]) vs. 8.8 [7.6], P = 0.004); time to first anus exhausting was significantly less in the AA group than in the control group (17.50 [6.00] vs. 20.42 [8.62], P = 0.020). CONCLUSIONS: AA combined with conventional anti-vomiting agents can alleviate PONV in female patients after LSG, and AA can promote gastrointestinal exhaustion. TRIAL REGISTRATION: The trial has been registered in the Chinese Clinical Trial Registry (ChiCTR) with the registration no. ChiCTR2100047381 on June 13, 2021.

Low distortion reversible database watermarking based on hybrid intelligent algorithm.

In many fields, such as medicine and the computer industry, databases are vital in the process of information sharing. However, databases face the risk of being stolen or misused, leading to security threats such as copyright disputes and privacy breaches. Reversible watermarking techniques ensure the ownership of shared relational databases, protect the rights of data owners and enable the recovery of original data. However, most of the methods modify the original data to a large extent and cannot achieve a good balance between protection against malicious attacks and data recovery. In this paper, we proposed a robust and reversible database watermarking technique using a hash function to group digital relational databases, setting the data distortion and watermarking capacity of the band weight function, adjusting the weight of the function to determine the watermarking capacity and the level of data distortion, using firefly algorithms (FA) and simulated annealing algorithms (SA) to improve the efficiency of the search for the location of the watermark embedded and, finally, using the differential expansion of the way to embed the watermark. The experimental results prove that the method maintains the data quality and has good robustness against malicious attacks.

Attribute-based multi-user collaborative searchable encryption in COVID-19.

With the outbreak of COVID-19, the government has been forced to collect a large amount of detailed information about patients in order to effectively curb the epidemic of the disease, including private data of patients. Searchable encryption is an essential technology for ciphertext retrieval in cloud computing environments, and many searchable encryption schemes are based on attributes to control user's search permissions to protect their data privacy. The existing attribute-based searchable encryption (ABSE) scheme can only implement the situation where the search permission of one person meets the search policy and does not support users to obtain the search permission through collaboration. In this paper, we proposed a new attribute-based collaborative searchable encryption scheme in multi-user setting (ABCSE-MU), which takes the access tree as the access policy and introduces the translation nodes to implement collaborative search. The cooperation can only be reached on the translation node and the flexibility of search permission is achieved on the premise of data security. ABCSE-MU scheme solves the problem that a single user has insufficient search permissions but still needs to search, making the user's access policy more flexible. We use random blinding to ensure the confidentiality and security of the secret key, further prove that our scheme is secure under the Decisional Bilinear Diffie-Hellman (DBDH) assumption. Security analysis further shows that the scheme can ensure the confidentiality of data under chosen-keyword attacks and resist collusion attacks.

Decoding of human identity by computer vision and neuronal vision.

Extracting meaning from a dynamic and variable flow of incoming information is a major goal of both natural and artificial intelligence. Computer vision (CV) guided by deep learning (DL) has made significant strides in recognizing a specific identity despite highly variable attributes. This is the same challenge faced by the nervous system and partially addressed by the concept cells-neurons exhibiting selective firing in response to specific persons/places, described in the human medial temporal lobe (MTL) ⁠. Yet, access to neurons representing a particular concept is limited due to these neurons' sparse coding. It is conceivable, however, that the information required for such decoding is present in relatively small neuronal populations. To evaluate how well neuronal populations encode identity information in natural settings, we recorded neuronal activity from multiple brain regions of nine neurosurgical epilepsy patients implanted with depth electrodes, while the subjects watched an episode of the TV series "24". First, we devised a minimally supervised CV algorithm (with comparable performance against manually-labeled data) to detect the most prevalent characters (above 1% overall appearance) in each frame. Next, we implemented DL models that used the time-varying population neural data as inputs and decoded the visual presence of the four main characters throughout the episode. This methodology allowed us to compare "computer vision" with "neuronal vision"-footprints associated with each character present in the activity of a subset of neurons-and identify the brain regions that contributed to this decoding process. We then tested the DL models during a recognition memory task following movie viewing where subjects were asked to recognize clip segments from the presented episode. DL model activations were not only modulated by the presence of the corresponding characters but also by participants' subjective memory of whether they had seen the clip segment, and by the associative strengths of the characters in the narrative plot. The described approach can offer novel ways to probe the representation of concepts in time-evolving dynamic behavioral tasks. Further, the results suggest that the information required to robustly decode concepts is present in the population activity of only tens of neurons even in brain regions beyond MTL.

New Method for Quantitative Prediction of Liquid Flowback Based on the Capillary Bundle Model.

Liquid invasion damage plays a main role in the formation damage of low-permeability sandstone reservoirs. The long-term retention of working fluid in the formation will cause serious water blocking damage. In order to research the quantitative prediction of liquid flowback in low-permeability sandstone reservoirs, a new method for quantitative prediction of liquid flowback based on the capillary bundle model was proposed, which took into account the boundary layer effect. Besides, taking the low-permeability sandstone samples of Penglaizhen formation in the Sichuan basin as an example, the quantitative prediction of liquid flowback was carried out. Finally, a series of experiments including gas displacement experiment and nuclear magnetic resonance experiment were conducted to examine the validation of the new method for quantitative prediction of liquid flowback. The study indicates that the results of quantitative prediction were in good agreement with the experimental results. Liquid flowback is closely related to pore structure, boundary layer effect, and displacement pressure in low-permeability sandstone reservoirs. For the sandstone sample with a permeability of 5.5 mD, most of the liquid could be displaced out at 1 MPa, and liquid saturation in the sandstone sample tends to be stable at 32%; for the sandstone sample with a permeability of 0.0349 mD, liquid flowback process is more durable, thereby the cumulative mass of liquid flowback and liquid saturation change gradually, and liquid saturation tends to be stable at 55%. This study not only provides an insight into the microscope mechanisms of liquid flowback but also predicts the cumulative mass of liquid flowback and liquid saturation accurately.

Hyperinsulinemic Hypoglycemia after Bariatric Surgery.

Postprandial hyperinsulinemic hypoglycemia (PHH) is one of the serious complications after bariatric surgery, it can lead life-threatening neuroglycopenic symptoms, such as seizures, disorientation, impairment of version and loss of consciousness without any premonitory. The presentation, prevalence, diagnosis, pathology and treatment are reviewed in this summary.

Intestinal Epithelial Cells-Derived Hypoxia-Inducible Factor-1α Is Essential for the Homeostasis of Intestinal Intraepithelial Lymphocytes.

Hif-1α is a master regulator which involved in the transcriptional regulation of anti-inflammatory or cellular responding to hypoxia. Previous work shows that the absence of Hif-1α results in the destruction of intestinal epithelial cell (IEC) and abnormalities of intestinal barrier function. However, we know very little about other functions of Hif-1α on intestinal intraepithelial lymphocyte (IEL). Therefore, we generated a transgenic mouse (Hif1-α ΔIEC mice), which was knocked out Hif1-α specifically in IECs, to study the effect of Hif1-α on IEL. IELs were isolated from the small intestine and colon of mice, respectively, and examined by flow cytometry and quantitative real-time PCR. All the cytokines expression was detected by quantitative real-time PCR. The NSAID enteropathy was induced by gavaged with 5 mg/kg indomethacin and the experimental colitis was induced by administration of 2.5% DSS. We found that the number of IELs is increased in Hif1-α ΔIEC mice. It is showed that knockout of Hif1-α in IECs led to significant changes in IEL phenotype, including a marked decline in the CD8αα+ and TCRγδ+ population. The reduction of CD8αα+ IELs is accompanied by increased apoptosis, decreased proliferation and weakened migration in Hif1-α ΔIEC mice. Moreover, absence of intestinal epithelial Hif1-α markedly changed the population of IELs in NSAID-induced small intestinal injury and increased susceptibility to dextran sulfate sodium-induced colitis. In summary, our results first time demonstrate that IEC-derived Hif1-α is essential for maintaining IELs homeostasis and intestinal microbiota.

Recurrent computations for visual pattern completion.

Making inferences from partial information constitutes a critical aspect of cognition. During visual perception, pattern completion enables recognition of poorly visible or occluded objects. We combined psychophysics, physiology, and computational models to test the hypothesis that pattern completion is implemented by recurrent computations and present three pieces of evidence that are consistent with this hypothesis. First, subjects robustly recognized objects even when they were rendered <15% visible, but recognition was largely impaired when processing was interrupted by backward masking. Second, invasive physiological responses along the human ventral cortex exhibited visually selective responses to partially visible objects that were delayed compared with whole objects, suggesting the need for additional computations. These physiological delays were correlated with the effects of backward masking. Third, state-of-the-art feed-forward computational architectures were not robust to partial visibility. However, recognition performance was recovered when the model was augmented with attractor-based recurrent connectivity. The recurrent model was able to predict which images of heavily occluded objects were easier or harder for humans to recognize, could capture the effect of introducing a backward mask on recognition behavior, and was consistent with the physiological delays along the human ventral visual stream. These results provide a strong argument of plausibility for the role of recurrent computations in making visual inferences from partial information.

Effect of Bulk MoS2 on the Metabolic Profile of Yeast.

MoS2, a kind of two-dimensional material with unique performances, has been widely used in many fields. However, an in-depth understanding of its toxicity is still needed, let alone its effects on the environmental microorganism. Herein, we used different methods, including metabolomics technology, to investigate the influence of bulk MoS2 (BMS) on yeast cells. The results indicated that high concentrations (1 mg/L and more) of BMS could destroy cell membrane and induce ROS accumulation. When exposed to a low concentration of BMS (0.1 mg/L), the intracellular concentrations of many metabolites (e.g., fumaric acid, lysine) increased. However, most of their concentrations descended significantly as the yeast cells were treated with BMS of high concentrations (1 mg/L and more). Metabolomics analysis further revealed that exposure to high concentrations of BMS could significantly affect some metabolic pathways such as amino acid and citrate cycle related metabolism. These findings will be beneficial for MoS2 toxicity assessment and further applications.

Predicting episodic memory formation for movie events.

Episodic memories are long lasting and full of detail, yet imperfect and malleable. We quantitatively evaluated recollection of short audiovisual segments from movies as a proxy to real-life memory formation in 161 subjects at 15 minutes up to a year after encoding. Memories were reproducible within and across individuals, showed the typical decay with time elapsed between encoding and testing, were fallible yet accurate, and were insensitive to low-level stimulus manipulations but sensitive to high-level stimulus properties. Remarkably, memorability was also high for single movie frames, even one year post-encoding. To evaluate what determines the efficacy of long-term memory formation, we developed an extensive set of content annotations that included actions, emotional valence, visual cues and auditory cues. These annotations enabled us to document the content properties that showed a stronger correlation with recognition memory and to build a machine-learning computational model that accounted for episodic memory formation in single events for group averages and individual subjects with an accuracy of up to 80%. These results provide initial steps towards the development of a quantitative computational theory capable of explaining the subjective filtering steps that lead to how humans learn and consolidate memories.

Cascade of neural processing orchestrates cognitive control in human frontal cortex.

Rapid and flexible interpretation of conflicting sensory inputs in the context of current goals is a critical component of cognitive control that is orchestrated by frontal cortex. The relative roles of distinct subregions within frontal cortex are poorly understood. To examine the dynamics underlying cognitive control across frontal regions, we took advantage of the spatiotemporal resolution of intracranial recordings in epilepsy patients while subjects resolved color-word conflict. We observed differential activity preceding the behavioral responses to conflict trials throughout frontal cortex; this activity was correlated with behavioral reaction times. These signals emerged first in anterior cingulate cortex (ACC) before dorsolateral prefrontal cortex (dlPFC), followed by medial frontal cortex (mFC) and then by orbitofrontal cortex (OFC). These results disassociate the frontal subregions based on their dynamics, and suggest a temporal hierarchy for cognitive control in human cortex.

Spatiotemporal dynamics underlying object completion in human ventral visual cortex.

Natural vision often involves recognizing objects from partial information. Recognition of objects from parts presents a significant challenge for theories of vision because it requires spatial integration and extrapolation from prior knowledge. Here we recorded intracranial field potentials of 113 visually selective electrodes from epilepsy patients in response to whole and partial objects. Responses along the ventral visual stream, particularly the inferior occipital and fusiform gyri, remained selective despite showing only 9%-25% of the object areas. However, these visually selective signals emerged ∼100 ms later for partial versus whole objects. These processing delays were particularly pronounced in higher visual areas within the ventral stream. This latency difference persisted when controlling for changes in contrast, signal amplitude, and the strength of selectivity. These results argue against a purely feedforward explanation of recognition from partial information, and provide spatiotemporal constraints on theories of object recognition that involve recurrent processing.

Decrease in gamma-band activity tracks sequence learning.

Learning novel sequences constitutes an example of declarative memory formation, involving conscious recall of temporal events. Performance in sequence learning tasks improves with repetition and involves forming temporal associations over scales of seconds to minutes. To further understand the neural circuits underlying declarative sequence learning over trials, we tracked changes in intracranial field potentials (IFPs) recorded from 1142 electrodes implanted throughout temporal and frontal cortical areas in 14 human subjects, while they learned the temporal-order of multiple sequences of images over trials through repeated recall. We observed an increase in power in the gamma frequency band (30-100 Hz) in the recall phase, particularly in areas within the temporal lobe including the parahippocampal gyrus. The degree of this gamma power enhancement decreased over trials with improved sequence recall. Modulation of gamma power was directly correlated with the improvement in recall performance. When presenting new sequences, gamma power was reset to high values and decreased again after learning. These observations suggest that signals in the gamma frequency band may play a more prominent role during the early steps of the learning process rather than during the maintenance of memory traces.

Low error discrimination using a correlated population code.

We explored the manner in which spatial information is encoded by retinal ganglion cell populations. We flashed a set of 36 shape stimuli onto the tiger salamander retina and used different decoding algorithms to read out information from a population of 162 ganglion cells. We compared the discrimination performance of linear decoders, which ignore correlation induced by common stimulation, with nonlinear decoders, which can accurately model these correlations. Similar to previous studies, decoders that ignored correlation suffered only a modest drop in discrimination performance for groups of up to ∼30 cells. However, for more realistic groups of 100+ cells, we found order-of-magnitude differences in the error rate. We also compared decoders that used only the presence of a single spike from each cell with more complex decoders that included information from multiple spike counts and multiple time bins. More complex decoders substantially outperformed simpler decoders, showing the importance of spike timing information. Particularly effective was the first spike latency representation, which allowed zero discrimination errors for the majority of shape stimuli. Furthermore, the performance of nonlinear decoders showed even greater enhancement compared with linear decoders for these complex representations. Finally, decoders that approximated the correlation structure in the population by matching all pairwise correlations with a maximum entropy model fit to all 162 neurons were quite successful, especially for the spike latency representation. Together, these results suggest a picture in which linear decoders allow a coarse categorization of shape stimuli, whereas nonlinear decoders, which take advantage of both correlation and spike timing, are needed to achieve high-fidelity discrimination.

Face recognition: vision and emotions beyond the bubble.

A new study of how neurons in the human amygdala represent faces and their component features argues for a holistic representation.

Primary gastric signet ring cell carcinoma presenting as cardiac tamponade.

Primary gastric signet ring cell carcinoma presenting as cardiac tamponade is difficult to diagnosis early. Patients are generally asymptomatic until the disease is advanced. General practitioners usually focus on the initial symptoms related to pericarditis and pericardial effusion. We report a case of signet-ring cell carcinoma of the stomach presenting as cardiac tamponade with pericarditis and pericardial effusion but without any gastrointestinal symptoms. A 49-year old woman was admitted because of progressive dyspnea and cough. Chest X-ray revealed an increased cardiothoracic ratio and a small amount of bilateral pleural effusion. Two dimensional ultrasonographic echocardiography pericardial effusions with atrial and right ventricular early diastolic collapse were found, establishing the diagnosis of cardiac tamponade. Pericardiocentesis was performed and 420 mL of bloody fluid was taken. The patient died of respiratory failure and cardiac arrest on October 28, 2009. Post-mortem examination revealed diffuse gastric mucosa erosion and edema with stomach mucosa incrassation in the greater curvature. The primary lesion was histopathologically diagnosed as signet-ring cell carcinoma of the stomach.