bluuebunny/crossref_metadata_2025_split huggingface dataset:
PCK1-mediated glycogenolysis facilitates ROS clearance and chemotherapy resistance in cervical cancer stem cells
Authors: Chen Xinxin , Yang Nan , Wang Ying , Yang Shuang , Peng Yuanhong 
Published: June 2024

AbstractCervical cancer, one of the most common gynecological cancers, is primarily caused by human papillomavirus (HPV) infection. The development of resistance to chemotherapy is a significant hurdle in treatment. In this study, we investigated the mechanisms underlying chemoresistance in cervical cancer by focusing on the roles of glycogen metabolism and the pentose phosphate pathway (PPP). We employed the cervical cancer cell lines HCC94 and CaSki by manipulating the expression of key enzymes PCK1, PYGL, and GYS1, which are involved in glycogen metabolism, through siRNA transfection. Our analysis included measuring glycogen levels, intermediates of PPP, NADPH/NADP+ ratio, and the ability of cells to clear reactive oxygen species (ROS) using biochemical assays and liquid chromatography–mass spectrometry (LC–MS). Furthermore, we assessed chemoresistance by evaluating cell viability and tumor growth in NSG mice. Our findings revealed that in drug-resistant tumor stem cells, the enzyme PCK1 enhances the phosphorylation of PYGL, leading to increased glycogen breakdown. This process shifts glucose metabolism towards PPP, generating NADPH. This, in turn, facilitates ROS clearance, promotes cell survival, and contributes to the development of chemoresistance. These insights suggest that targeting aberrant glycogen metabolism or PPP could be a promising strategy for overcoming chemoresistance in cervical cancer. Understanding these molecular mechanisms opens new avenues for the development of more effective treatments for this challenging malignancy.
Association of myosteatosis with short-term outcomes in patients with acute-on-chronic liver failure
Authors: Geng Nan , Kong Ming , Zhang Jiateng , Chen Huina , Xu Manman , Song Wenyan , Chen Yu , Duan Zhongping 
Published: June 2024

AbstractSarcopenia (low muscle mass, i.e., quantity) is associated with poor clinical outcomes in patients with acute-on-chronic liver failure (ACLF). In this study, we aimed to illustrate the clinical prognostic value of myosteatosis (muscle fat infiltration) for short-term mortality in patients with ACLF. We retrospectively enrolled consecutive patients with ACLF between January 2019 and January 2022. Computed tomography-based body composition analysis was performed at the third lumbar vertebral level to determine skeletal muscle radiation attenuation. Fine and Gray’s competing risk regression model, with liver transplantation as a competing risk, was used to assess the factors associated with 90-day mortality. A total of 431 patients with ACLF were included. Myosteatosis and sarcopenia were observed in 261 (60.6%) and 87 (20.2%) patients, respectively. Competitive risk regression showed that age (HR 1.021, 95% CI 1.000–1.043, P = 0.042), APASL ACLF Research Consortium (AARC) score (HR 1.498, 95% CI 1.312–1.710, P < 0.001), and sarcopenia (HR 1.802, 95% CI 1.062–3.060, P = 0.029) were independently associated with increased 90-day mortality. Subgroup analysis of male patients with HBV-ACLF revealed that myosteatosis (HR 2.119, 95% CI 1.101–4.078, P = 0.025) was promising prognostic factors for 90-day mortality after being adjusted for ascites, acute kidney injury, AARC score, and sarcopenia. Myosteatosis is predictive of short-term outcomes in male patients with HBV-ACLF. Our results emphasise the importance of focusing on muscle fat infiltration in patients with HBV-ACLF. Further studies are warranted to investigate the underlying mechanisms and potential therapies for myosteatosis.
Force and power requirement for development of cumin harvester: a dynamic approach
Authors: Kumar Mohit , Sahoo Pramod Kumar , Kushwaha Dilip Kumar , Mani Indra , Pradhan Nrusingh Charan , Patel Abhishek , Tariq Aqil , Ullah Sajid , Soufan Walid 
Published: June 2024

AbstractAn experimental setup was developed for simulating the field conditions to determine the force and power required for cutting cumin crops in dynamic conditions. The effect of cutter bar speeds, forward speeds, and blade type on cutting force and power requirement for cutting cumin were also studied. Experiments were carried out at three levels: cutter bar speeds, forward speeds, and blade type. The results showed that all the factors significantly affected cutting force. The cutting force followed a decreasing trend with the increase in cutter bar speed. Whereas it followed an increasing trend with the increase in forward speed. The maximum cutting force for all three blades was observed at a cutter bar speed of 2.00 strokes.s-1 and forward speed of 0.46 m.s−1. The idle power and actual power required for cutting the cumin crop were also determined based on the cutting force. The results obtained were validated by the power drawn from the power source while operating the cutter bar blades. The R2 values for Blade-B1, Blade-B2, and Blade-B3 were 0.90, 0.82, and 0.88, respectively. The cutting force was primarily affected by the cutter bar speed, resulting in PCR values of 74.20%, 82.32%, and 81.75% for Blade-B1, Blade-B2, and Blade-B3, respectively, followed by the forward speed, which also had an impact on PCR values of 16.60%, 15.27%, and 18.25% for Blade-B1, Blade-B2, and Blade-B3, respectively. The cutting force for Blade-B1, Blade-B2, and Blade-B3 varied from 15.96 to 58.97 N, 21.08 to 76.64 N, and 30.22 to 85.31, respectively, for the selected range of cutter bar speed and forward speed. Blade-B1 had 18 and 30% less power consumption than Blade-B2 and Blade-B3, respectively.
SACNN‐IDS: A self‐attention convolutional neural network for intrusion detection in industrial internet of things
Authors: Qathrady Mimonah Al , Ullah Safi , Alshehri Mohammed S. , Ahmad Jawad , Almakdi Sultan , Alqhtani Samar M. , Khan Muazzam A. , Ghaleb Baraq 
Published: June 2024

AbstractIndustrial Internet of Things (IIoT) is a pervasive network of interlinked smart devices that provide a variety of intelligent computing services in industrial environments. Several IIoT nodes operate confidential data (such as medical, transportation, military, etc.) which are reachable targets for hostile intruders due to their openness and varied structure. Intrusion Detection Systems (IDS) based on Machine Learning (ML) and Deep Learning (DL) techniques have got significant attention. However, existing ML and DL‐based IDS still face a number of obstacles that must be overcome. For instance, the existing DL approaches necessitate a substantial quantity of data for effective performance, which is not feasible to run on low‐power and low‐memory devices. Imbalanced and fewer data potentially lead to low performance on existing IDS. This paper proposes a self‐attention convolutional neural network (SACNN) architecture for the detection of malicious activity in IIoT networks and an appropriate feature extraction method to extract the most significant features. The proposed architecture has a self‐attention layer to calculate the input attention and convolutional neural network (CNN) layers to process the assigned attention features for prediction. The performance evaluation of the proposed SACNN architecture has been done with the Edge‐IIoTset and X‐IIoTID datasets. These datasets encompassed the behaviours of contemporary IIoT communication protocols, the operations of state‐of‐the‐art devices, various attack types, and diverse attack scenarios.
Comparison of Patients Based on Their Self-Selected Discharge Pathway after Total Knee Arthroplasty at an Ambulatory Surgical Center
Authors: Palmsten Allison , Haynes Amy L. , Ryan Jaclyn M. , Pittman Gavin T. , Huang Der-Chen T. , Obermeier Michael , Chmielewski Terese L. 
Published: June 2024

AbstractOutpatient total knee arthroplasty (TKA) is being performed more frequently in ambulatory surgical centers (ASCs) to decrease the cost of care. Discharge pathways include 23-hour observation (OBSERVATION) or same-day discharge home (HOME), which differ in postoperative medical supervision. Few studies allow patients to self-select their discharge pathway. This study compared patient variables between self-selected OBSERVATION or HOME discharge after TKA at an ASC. We hypothesized that age, sex, and distance lived from the ASC would differ between discharge pathways. Clinical and patient-reported outcomes were explored.A chart review identified 130 patients with TKA at an ASC between November 2017 and December 2019. Patients self-selected OBSERVATION or HOME during a preoperative physician visit. Patient variables obtained from the electronic medical record were age, sex, race/ethnicity, marital status, body mass index, diabetic status, American Society of Anesthesiologists (ASA) class, distance lived from the ASC, anesthesia type, procedure time, and time in the postanesthesia recovery unit. Clinical outcomes (knee range of motion, infection rate, and reoperation rate) and patient-reported outcomes (Knee Injury and Osteoarthritis Outcome Score, Joint Replacement [KOOS, JR]; Oxford Knee Score [OKS]) were collected at either 6 or 12 weeks postsurgery. Variables were compared between groups.Pathway selection was n = 70 OBSERVATION and n = 60 HOME, and all patients completed their self-selected discharge pathway. Age and proportion of females were significantly higher in OBSERVATION than in HOME (61.3 ± 3.5 vs. 58.5 ± 5.4 years, 85.7 vs. 65.0%, respectively; p < 0.05). Distance lived from the ASC tended to be greater in OBSERVATION than HOME (22.1 ± 24.6 vs. 15.3 ± 10.1 miles, p = 0.056). Across groups, clinical outcomes were favorable (i.e., >88% met the 6-week knee flexion milestone, 1.9% infection rate, and 3.1% manipulation under anesthesia), and the preoperative to 12-week postoperative change in KOOS, JR and OKS scores met the minimal clinically important difference.Older age, female sex, and farther distance lived from the ASC may influence patients to select OBSERVATION over HOME discharge following TKA at an ASC. No robust differences were found in early outcomes.
Clinical Characteristics of Different Human Cytomegalovirus Glycoprotein N Genotypes among Child Patients in China
Authors: Li Huamei , He Lin , Wang Bing , Tao Ran , Shang Shiqiang 
Published: June 2024

Abstract
Objective This study aimed to investigate the relationship between clinical characteristics and human cytomegalovirus (HCMV) glycoprotein N (gN) genotypes in children.
Methods HCMV gN gene polymorphisms in 544 patients were analyzed using semi-nested polymerase chain reaction and restriction fragment length polymorphism.
Results The highest proportion was observed for the gN3a genotype (126/544, 23.2%). The proportion of children with mixed infections presenting with the hepatitis phenotype (65/69, 94.2%) was significantly higher than that of each gN genotype, except for gN3b (34/43, 79.1%, all p < 0.0083). Patients infected with 4b genotype (56/56, 100%) had a significantly higher proportion of anemia symptoms than those infected with all other gN genotypes (all p < 0.0083). There were also significant differences in the proportion of patients infected with different gN genotypes who presented with clinical features, such as jaundice, pneumonia, and thrombocytopenic purpura. Patients with the gN2 genotype had significantly higher albumin levels than those with the gN3a genotype (p = 0.042).
Conclusion The clinical phenotypes and laboratory indicators of HCMV infection in children with different gN genotypes are somewhat different, suggesting that precise typing of gN genes has clinical value.
Unraveling the psychological impact of spatial cybertext environments on speech intent
Authors: Rahardi R Kunjana , Rahmat Wahyudi , Tiawati Refa Lina , Setyaningsih Yuliana 
Published: June 2024

AbstractThis cyberpragmatic study investigates the correlation between spatial multimodal cybertext environments and their psychological impact on speech intent. The research delves into speech fragments in diverse cybertextual contexts across social media platforms. The methodology involves data identification, transcription, classification, and typification. Similarly, looking at things, the study shows that the physical settings of cybertexts have a big effect on the everyday meanings of words, acting as background, determinant, emphasis enhancer, reinforcement, illustration, and signal for speech intent. The research explores the distinct role of each category in shaping speech intention within spatial cybertexts, underscoring how these insights can facilitate effective communication and their psychological impact on speech intent, particularly for language learners on social media platforms.
Binary classification of dead detector elements in flat panel detectors using convolutional neural networks
Authors: Box Jon , Schnell Erich , Rutel Isaac 
Published: June 2024

Abstract

Objective. Medical physicists routinely perform quality assurance on digital detection systems, part of which involves the testing of flat panel detectors. Flat panels may degrade over time as an increasing number of individual detector elements begin to malfunction. The pixels that correspond to these elements are corrected for using information elsewhere in the detector system, however these corrected elements still constitute a loss in image quality for the system as a whole. These correction methods, as well as the location and number of dead detector elements, are often only available to the vendor of the digital detection system, but not to the medical physicist responsible for the quality assurance of the system. Approach. We greatly expand upon a previous work by providing a novel technique for classifying dead detector elements at single pixel resolution. We also demonstrate that this technique can be trained on one detector, and then tested and validated on another with moderate success, which demonstrates some ability to generalize to different detectors. The technique requires 3 flat field, or ‘noise’, images to be taken to predict the dead detector element maps for the system. Main results. Models using only for-processing pixel data were unable to successfully generalize from one detector to the other. Models preprocessed using the standard deviation across three for-processing images were able to classify dead detector element maps with an F1 score ranging from 0.4527 to 0.8107 and recall ranging from 0.5420 to 0.9303 with better performance, on average, observed using the low exposure data set. Significance. Many physicists do not have access to the dead detector maps for their diagnostic digital radiography systems. CNNs are capable of predicting the dead detector maps of flat panel detectors with single pixel resolution. Physicists can implement this tool by acquiring three flat field images and then inputting them into the model. Model performance saw a marginal increase when trained on the low exposure set data, as opposed to the high exposure set data, indicating high exposure, low relative noise images may not be necessary for optimal performance. Model performance across detectors manufactured by different vendors requires further investigation.
Epidemiology and Prognostic Factors Analysis of Electrical Injuries in Shaanxi, China: A Single-Center Observational Study of 385 Cases
Authors: Zhao Huaqiang , Lei Zhanjun , Yang Ming , Li Xueyong , Tang Jiezhang , Dong Yuchen , Feng Jian , Bian Yongqian 
Published: June 2024

Abstract
The objective of this research is to investigate the epidemiological features of electrical injuries in Shaanxi Province, China, examine their prognosis, and ascertain the factors that impact the outcomes. Telephone follow-ups were conducted with patients with electrical injuries at our hospital between 2011 and 2021, yielding the following results: Most electrical injuries occur in males (94.3%) and younger or middle-aged individuals. The most common voltages involved are 220 and 380 V. Since 2016, there has been a 20.1% annual decrease in electrical injuries, with most cases occurring from April to September. Patients typically undergo 1 surgical procedure (0.3), with a 14.8% amputation rate and an average hospital stay of 21 days (9.43). A total of 1.8% of patients with electrical injuries have died, 17.1% have permanent nerve damage, and 10.8% need help with daily tasks; 18.5% have psychological issues, and 9.6% have posttraumatic stress disorder; and 93.7% return-to-work in an average of 6 months (2.12). Amputation risk is influenced by voltage, muscle injury, and current pathway; skin grafting risk is mainly due to voltage. Heart injuries are affected by unconsciousness and current pathways; labor loss risk factors include voltage, falls from heights, and muscle injury; and nerve damage is linked to muscle injury. Cataract development risk is associated with electric shock to the head and neck. It is crucial to address the psychological well-being of patients and provide necessary support. Patient input should be taken into account when deciding on treatment for nonfunctional limbs. Physicians should evaluate prognostic factors and provide appropriate treatment to enhance patient outcomes.
Burn Center Verification and Safety Net Status: Are There Differences in Discharge to Inpatient Rehabilitation?
Authors: Lakhlani Devi , Steeman Samantha , Stanton Eloise W , Sheckter Clifford 
Published: June 2024

Abstract
Discharge to acute rehabilitation following a major burn injury is crucial for patient recovery and quality of life. However, barriers to acute rehabilitation, including race and payor type, impede access. The effect of burn center organizational structure on discharge disparities remains unknown. This study aims to investigate associations between patient demographics, burn center factors, and discharge to acute rehabilitation on a population level. Using the California Healthcare Access and Information Database, 2009-2019, all inpatient encounters at verified and non-verified burn centers were extracted. The primary outcome was the proportion of patients discharged to acute rehabilitation. Key covariates included age, race, burn center safety net status, diagnosis-related group, American Burn Association (ABA) verification status, and American College of Surgeons Level 1 trauma center designation. Logistic regression and mixed-effects modeling were performed, with Bonferroni adjustment for multiple testing. Among 27 496 encounters, 0.8% (228) were discharged to inpatient rehabilitation. By race/ethnicity, the proportion admitted to inpatient rehabilitation was 0.9% for White, 0.6% for Black, 0.7% for Hispanic, and 1% for Asian. After adjusting for burn severity and age, notable predictors for discharge to inpatient rehabilitation included Medicare as payor (OR 0.30-0.88, P = .015) compared to commercial insurance, trauma center status (OR 1.45-3.43, P &lt; .001), ABA verification status (OR 1.16-2.74, P = .008), and safety net facility status (OR 1.09-1.97, P = .013). Discharge to inpatient rehabilitation varies by race, payor status, and individual burn center. Verified and safety net burn centers had more patients discharge to inpatient rehabilitation adjusted for burn severity and demographics.
(333) SEXUAL FUNCTION RECOVERY FOLLOWING OPEN AND ROBOTIC RADICAL PROSTATECTOMY: RESULTS OF AN ACADEMIC PENILE REHABILITATION PROGRAM
Authors: Di Nauta Dr Michele , Falagario Dr Ugo G , Ricapito Dr Anna , Annese Dr Pasquale , Rubino Dr Matteo , Busetto Prof Gian M , Cormio Prof Luigi , Carrieri Prof Giuseppe , Bettocchi Carlo 
Published: June 2024

Abstract

Objectives
Radical prostatectomy (RP) is the gold standard treatment for clinically localized prostate cancer (PCa) in patients with a life expectancy 10 yr. Notwithstanding improvements in surgical techniques, erectile dysfunction (ED) is a common sequela of RP. The aim of the present study was to evaluate the effect of early penile rehabilitation in a dedicated Penile Rehabilitation Program on both assisted and unassisted erectile function (EF) in men who developed ED after open and robotic RP.

Methods
All patients undergoing open or robotic RP and early penile rehabilitation were included in the present study. All patients were treated and followed up at a single academic institution in a dedicated Penile Rehabilitation Program. Treatment included phosphodiesterase type 5 inhibitors (PDE5Is), intracavernous injections and vacuum erection devices (VEDs). EF recovery was defined as IIEF&gt;20. Data were prospectively collected and retrospectively reviewed. Kaplan Mayer curves were used to evaluate EF recovery.

Results
A total of 570 patients met the inclusion criteria. 397 patients underwent rehabilitation. 168 (42.3%) underwent robotic RP. Unilateral and bilateral nerve sparing was performed in 38 (9.6%) and 116 (29.2%) patients respectively.
A combination of PDE5I and intracavernous injections was the most frequently used first line treatment (233, 59%). VEDs were used in 52 patients in addition to PDE5I and intracavernous injections (39, 10%) or intracavernous injections (23, 6%). In patients with a preoperative IIEF&gt;21, assisted and unassisted EF recovery rates were 78% and 36% respectively.
In patients with a preoperative IIEF&lt;16, assisted and unassisted EF recovery rates were 46% and 18% respectively. Sub analysis showed a moderate benefit of penile rehabilitation also in patients with a preoperative IIEF&lt;16 undergoing bilateral nerve sparing RP.

Conclusions
Intensive penile rehabilitation programs improves EF recovery in patients undergoing radical prostatectomy. Preservation of Neurovascular bundles should be attempted also in patients with preoperative ED.

Conflicts of Interest
No conflicts of interest.