Complex therapy for hepatic trauma

Background:Hepatic trauma is a major cause of death in abdominal injury patients.. This study was aimed at investigating the outcome of management of 197 patients presenting with hepatic injuries.Methods:This was a rgtrospective study of all patients treated for hepatic injuries at Oilu Hospital from January 1980 to January 1999 and at Dodoma Regional Hospital from January 1990 to January 2001.Seven patients were treated non-surgically while 188 had surgery. Conservative treatment included absolute bed rest, replacement and stabilization of the blood capacity, anti-inflammation drugs and styptic. Surgical procedures for patients with grade I11 and IV hepatic trauma included packing with omentum and repair of liver lacerations, debridment or irregular hepatectomy under Pringle's maneuver, perihepatic tamponade with or without selective ligation of hepatic artery and post hepatic vein repair together with T-tube and perihepatic drainage.Results: There were 30 deaths (15.3% mortality rate). All the seven patients treated conservatively survived. The main cause of death was exsanguination with or without coagulopathy, multiple organ failure (MOSF) and associated injuries. Conclusion:The basic operative principles for liver injuries are thorough debridment and haemostasis, elimination of bile leakage and unobstructed drainage.Key words: Abdominal injury, hepatic injury, therapeutics, and surgery

Check Me If You Can: Detecting ChatGPT-Generated Academic Writing using CheckGPT

With ChatGPT under the spotlight, utilizing large language models (LLMs) for academic writing has drawn a significant amount of discussions and concerns in the community. While substantial research efforts have been stimulated for detecting LLM-Generated Content (LLM-content), most of the attempts are still in the early stage of exploration. In this paper, we present a holistic investigation of detecting LLM-generate academic writing, by providing a dataset, evidence, and algorithms, in order to inspire more community effort to address the concern of LLM academic misuse. We first present GPABenchmark, a benchmarking dataset of 600,000 samples of human-written, GPT-written, GPT-completed, and GPT-polished abstracts of research papers in CS, physics, and humanities and social sciences (HSS). We show that existing open-source and commercial GPT detectors provide unsatisfactory performance on GPABenchmark, especially for GPT-polished text. Moreover, through a user study of 150+ participants, we show that it is highly challenging for human users, including experienced faculty members and researchers, to identify GPT-generated abstracts. We then present CheckGPT, a novel LLM-content detector consisting of a general representation module and an attentive-BiLSTM classification module, which is accurate, transferable, and interpretable. Experimental results show that CheckGPT achieves an average classification accuracy of 98% to 99% for the task-specific discipline-specific detectors and the unified detectors. CheckGPT is also highly transferable that, without tuning, it achieves ~90% accuracy in new domains, such as news articles, while a model tuned with approximately 2,000 samples in the target domain achieves ~98% accuracy. Finally, we demonstrate the explainability insights obtained from CheckGPT to reveal the key behaviors of how LLM generates texts

New threats to health data privacy

<p>Abstract</p> <p>Background</p> <p>Along with the rapid digitalization of health data (e.g. Electronic Health Records), there is an increasing concern on maintaining data privacy while garnering the benefits, especially when the data are required to be published for secondary use. Most of the current research on protecting health data privacy is centered around data de-identification and data anonymization, which removes the identifiable information from the published health data to prevent an adversary from reasoning about the privacy of the patients. However, published health data is not the only source that the adversaries can count on: with a large amount of information that people voluntarily share on the Web, sophisticated attacks that join disparate information pieces from multiple sources against health data privacy become practical. Limited efforts have been devoted to studying these attacks yet.</p> <p>Results</p> <p>We study how patient privacy could be compromised with the help of today’s information technologies. In particular, we show that private healthcare information could be collected by aggregating and associating disparate pieces of information from multiple online data sources including online social networks, public records and search engine results. We demonstrate a real-world case study to show user identity and privacy are highly vulnerable to the attribution, inference and aggregation attacks. We also show that people are highly identifiable to adversaries even with inaccurate information pieces about the target, with real data analysis.</p> <p>Conclusion</p> <p>We claim that too much information has been made available electronic and available online that people are very vulnerable without effective privacy protection.</p

Chinese Medicines for Preventing and Treating Radiation-Induced Pulmonary Injury: Still a Long Way to Go

Thoracic radiotherapy is a mainstay of the treatment for lung, esophageal, and breast cancers. Radiation-induced pulmonary injury (RIPI) is a common side effect of thoracic radiotherapy, which may limit the radiotherapy dose and compromise the treatment results. However, the current strategies for RIPI are not satisfactory and may induce other side effects. Chinese medicines (CMs) have been used for more than a thousand years to treat a wide range of diseases, including lung disorders. In this review, we screened the literature from 2007 to 2017 in different online databases, including China National Knowledge Infrastructure (CNKI), Chongqing VIP, Wanfang, and PubMed; summarized the effectiveness of CMs in preventing and treating RIPI; explored the most frequently used drugs; and aimed to provide insights into potential CMs for RIPI. Altogether, CMs attenuated the risk of RIPI with an occurrence rate of 11.37% vs. 27.78% (P < 0.001) compared with the control groups. We also found that CMs (alone and combined with Western medical treatment) for treating RIPI exerted a higher efficacy rate than that of the control groups (78.33% vs. 28.09%, P < 0.001). In the screened literature, 38 CMs were used for the prevention and treatment of RIPI. The top five most frequently used CMs were Astragali Radix (with a frequency of 8.47%), Ophiopogonis Radix (with a frequency of 6.78%), Glycyrrhizae Radix et Rhizome (with a frequency of 5.08%), Paeoniae Radix Rubra (with a frequency of 5.08%), and Prunellae Spica (with a frequency of 5.08%). However, further high-quality investigations in CM source, pharmacological effects and underlying mechanisms, toxicological aspects, and ethical issues are warranted. Taken together, CMs might have a potential role in RIPI prevention and treatment and still have a long way to investigate

Research of Surfactant-polymer Flooding Response Characteristic and Mobility Optimization of J Oilfield in Bohai Bay

Surfactant-polymer flooding technology which used in J oilfield is still the first time in Bohai bay, the reference materials are very seldom for its response characteristic and project optimization. Since there’s no blank water flooding stage between polymer flooding and surfactant-polymer flooding in J oilfield, it’s difficult to accurately judge the response characteristic of production wells and injection wells by the conventional method; on the other side, as surfactant-polymer flooding gradually entered the end stage, the effect of decrease water and increase oil became worse, there’s urgently need to improve the effect of chemical flooding. Thus, the research of response characteristic and mobility optimization are conducted in this article. The water cut funnel method is used for the first time to recognize the response of the production wells in J oilfield, and to use the Hall curve method to recognize the response of the injection wells. Meanwhile, based on the idea of mobility control, the minimum polymer concentration which is needed to control the mobility of surfactant-polymer flooding is studied, and establish the mobility control template, the effect of the surfactant-polymer flooding is improved effectively by use of the template to guide the optimization of the polymer concentration, and daily production increase about 15% of J oilfield. The research can be used to guide and refer to other similar offshore oilfield development

UPOCR: Towards Unified Pixel-Level OCR Interface

In recent years, the optical character recognition (OCR) field has been proliferating with plentiful cutting-edge approaches for a wide spectrum of tasks. However, these approaches are task-specifically designed with divergent paradigms, architectures, and training strategies, which significantly increases the complexity of research and maintenance and hinders the fast deployment in applications. To this end, we propose UPOCR, a simple-yet-effective generalist model for Unified Pixel-level OCR interface. Specifically, the UPOCR unifies the paradigm of diverse OCR tasks as image-to-image transformation and the architecture as a vision Transformer (ViT)-based encoder-decoder. Learnable task prompts are introduced to push the general feature representations extracted by the encoder toward task-specific spaces, endowing the decoder with task awareness. Moreover, the model training is uniformly aimed at minimizing the discrepancy between the generated and ground-truth images regardless of the inhomogeneity among tasks. Experiments are conducted on three pixel-level OCR tasks including text removal, text segmentation, and tampered text detection. Without bells and whistles, the experimental results showcase that the proposed method can simultaneously achieve state-of-the-art performance on three tasks with a unified single model, which provides valuable strategies and insights for future research on generalist OCR models. Code will be publicly available

Emodin Induced SREBP1-Dependent and SREBP1-Independent Apoptosis in Hepatocellular Carcinoma Cells

Reynoutria multiflora (Thunb.) Moldenke (He Shou Wu) has been used for about 20 centuries as a Chinese medicinal herb for its activities of anticancer, anti-hyperlipidemia, and anti-aging. Previously, we found that He Shou Wu ethanol extract could induce apoptosis in hepatocellular carcinoma cells, and we also screened its active components. In this study, we investigated whether lowering lipid metabolism of emodin, a main active component in He Shou Wu, was associated with inhibitory effects in hepatocellular carcinoma cells. The correlation of apoptosis induction and lipid metabolism was investigated. The intrinsic apoptotic cell death, lipid production, and their signaling pathways were investigated in emodin-treated human hepatocellular carcinoma cells Bel-7402. The data showed that emodin triggered apoptosis in Bel-7402 cells. The mitochondrial membrane potential (ΔΨm) was reduced in emodin-treated Bel-7402 cells. We also found that emodin activated the expression of intrinsic apoptosis signaling pathway-related proteins, cleaved-caspase 9 and 3, Apaf 1, cytochrome c (CYTC), apoptosis-inducing factor, endonuclease G, Bax, and Bcl-2. Furthermore, the level of triglycerides and desaturation of fatty acids was reduced in Bel-7402 cells when exposed to emodin. Furthermore, the expression level of messenger RNA (mRNA) and protein of sterol regulatory element binding protein 1 (SREBP1) as well as its downstream signaling pathway and the synthesis and the desaturation of fatty acid metabolism-associated proteins (adenosine triphosphate citrate lyase, acetyl-CoA carboxylase alpha, fatty acid synthase (FASN), and stearoyl-CoA desaturase D) were also decreased. Notably, knock-out of SREBP1 in Bel-7402 cells was also found to induce less intrinsic apoptosis than did emodin. In conclusion, these results indicated that emodin could induce apoptosis in an SREBP1-dependent and SREBP1-independent manner in hepatocellular carcinoma cells

ZnO/Cu₂O heterojunction integrated fiber-optic biosensor for remote detection of cysteine

Indium tin oxide, semiconductor nanomaterial ZnO, and Cu2O were first loaded on the surface of the optical fiber to form an optical fiber probe. Large-volume macroscopic spatial light is replaced by an optical fiber path, and remote light injection is implemented. Based on the optical fiber probe, a photoelectrochemical biosensor was constructed and remote detection of cysteine was realized. In this tiny device, the optical fiber probe not only acts as a working electrode to react with the analyte but also directs the light exactly where it is needed. Simultaneously, the electrochemical behavior of cysteine on the surface of the working electrode is dominated by diffusion-control, which provides strong support for quantitative detection. Then, under the bias potential of 0 V, the linear range of the fiber-optic-based cysteine biosensor was 0.01∼1 μM, the regression coefficient (R2) value was 0.9943. In spiked synthetic urine, the detection of cysteine was also realized by the integrated biosensor. Moreover, benefiting from the low optical fiber loss, the new structure also possesses a unique remote detection function. This work confirms that photoelectrochemical biosensors can be integrated via optical fibers and retain comparable sensing performance. Based on this property, different materials can also be loaded on the surface of the optical fiber for remote detection of other analytes. It is expected to facilitate the research on fiber-optic-based integrated biosensors and show application prospects in diverse fields such as biochemical analysis and disease diagnosis.</p

Enforcing Secure and Privacy-Preserving Information Brokering in Distributed Information Sharing

Today’s organizations raise an increasing need for information sharing via on-demand access. Information Brokering Systems (IBSs) have been proposed to connect large-scale loosely-federated data sources via a brokering overlay, in which the brokers make routing decisions to direct client queries to the requested data servers. Many existing IBSs assume that brokers are trusted and thus only adopt server-side access control for data confidentiality. However, privacy of data location and data consumer can still be inferred from metadata (such as query and access control rules) exchanged within the IBS, but little attention has been put on its protection. In this article, we propose a novel approach to preserve privacy of multiple stakeholders involved in the information brokering process. We are among the first to formally define two privacy attacks, namely attribute-correlation attack and inference attack, and propose two countermeasure schemes automaton segmentation and query segment encryption to securely share the routing decision making responsibility among a selected set brokering servers. With comprehensive security analysis and experimental results, we show that our approach seamlessly integrates security enforcement with query routing to provide system-wide security with insignificant overhead