Up-regulation of non-photochemical quenching improves water use efficiency and reduces whole-plant water consumption under drought in Nicotiana tabacum.

Water supply limitations will likely impose increasing restrictions on future crop production, underlining a need for crops that use less water per mass of yield. Water use efficiency (WUE) therefore becomes a key consideration in developing resilient and productive crops. In this study, we hypothesized that it is possible to improve WUE under drought conditions via modulation of chloroplast signals for stomatal opening by up-regulation of non-photochemical quenching (NPQ). Nicotiana tabacum plants with strong overexpression of the PsbS gene encoding PHOTOSYSTEM II SUBUNIT S, a key protein in NPQ, were grown under differing levels of drought. The PsbS-overexpressing lines lost 11% less water per unit CO2 fixed under drought and this did not have a significant effect on plant size. Depending on growth conditions, the PsbS-overexpressing lines consumed from 4-30% less water at the whole-plant level than the corresponding wild type. Leaf water and chlorophyll contents showed a positive relation with the level of NPQ. This study therefore provides proof of concept that up-regulation of NPQ can increase WUE, and as such is an important step towards future engineering of crops with improved performance under drought.

Bagging Improves the Performance of Deep Learning-Based Semantic Segmentation with Limited Labeled Images: A Case Study of Crop Segmentation for High-Throughput Plant Phenotyping.

Advancements in imaging, computer vision, and automation have revolutionized various fields, including field-based high-throughput plant phenotyping (FHTPP). This integration allows for the rapid and accurate measurement of plant traits. Deep Convolutional Neural Networks (DCNNs) have emerged as a powerful tool in FHTPP, particularly in crop segmentation-identifying crops from the background-crucial for trait analysis. However, the effectiveness of DCNNs often hinges on the availability of large, labeled datasets, which poses a challenge due to the high cost of labeling. In this study, a deep learning with bagging approach is introduced to enhance crop segmentation using high-resolution RGB images, tested on the NU-Spidercam dataset from maize plots. The proposed method outperforms traditional machine learning and deep learning models in prediction accuracy and speed. Remarkably, it achieves up to 40% higher Intersection-over-Union (IoU) than the threshold method and 11% over conventional machine learning, with significantly faster prediction times and manageable training duration. Crucially, it demonstrates that even small labeled datasets can yield high accuracy in semantic segmentation. This approach not only proves effective for FHTPP but also suggests potential for broader application in remote sensing, offering a scalable solution to semantic segmentation challenges. This paper is accompanied by publicly available source code.

Molecular and Genetics-Based Systems for Tracing the Evolution and Exploring the Mechanisms of Human Norovirus Infections.

Human noroviruses (HuNoV) are major causes of acute gastroenteritis around the world. The high mutation rate and recombination potential of noroviruses are significant challenges in studying the genetic diversity and evolution pattern of novel strains. In this review, we describe recent advances in the development of technologies for not only the detection but also the analysis of complete genome sequences of noroviruses and the future prospects of detection methods for tracing the evolution and genetic diversity of human noroviruses. The mechanisms of HuNoV infection and the development of antiviral drugs have been hampered by failure to develop the infectious virus in a cell model. However, recent studies have demonstrated the potential of reverse genetics for the recovery and generation of infectious viral particles, suggesting the utility of this genetics-based system as an alternative for studying the mechanisms of viral infection, such as cell entry and replication.

Effects of branched-chain amino acid-rich supplementation on EWGSOP2 criteria for sarcopenia in older adults: a systematic review and meta-analysis.

PURPOSE: According to criteria recommended by the European Working Group on Sarcopenia in Older People 2 (EWGSOP2), we analyzed the effects of branched-chain amino acid (BCAA)-rich supplements on muscle strength, muscle mass, and physical performance in older people. METHODS: We searched PubMed, Embase, Cochrane Library, and CINAHL from inception until March 2021. Randomized controlled trials that examined the effect of BCAA-rich supplements on older people were included. Random-effects meta-analyses and sensitivity analyses were performed. Subgroup analyses were stratified by participant and supplementation characteristics. Meta-regression analyses were performed to examine the effect of continuous variables. RESULTS: Thirty-five studies were included in this meta-analysis. Quality assessment revealed that 14 of 35 RCTs had some potential bias. The overall standardized mean difference (SMD) in muscle strength, muscle mass, and physical performance between the supplement and control groups was 0.35 (95% CI = [0.15, 0.55], P = 0.0007), 0.25 (95% CI = [0.10, 0.40], P = 0.0008), and 0.29 (95% CI = [0.00, 0.57], P = 0.05), respectively. Subgroup analysis revealed that essential amino acid supplementation improved handgrip strength more significantly than whey protein supplementation in older people. Meta-regression analysis revealed a significant linear relationship between improvements in handgrip strength and body mass index. CONCLUSIONS: BCAA-rich supplementation by older people may have beneficial effects on muscle mass and strength. However, the included studies had high heterogeneity, and the results must be interpreted with caution. PROSPERO REGISTRATION NUMBER: CRD42020206674.

Analgesic Effects of Regional Analgesic Techniques in Pediatric Inguinal Surgeries: A Systematic Review and Network Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Various regional analgesic techniques have been used in pediatric inguinal surgery to facilitate postoperative recovery. However, each technique's relative performance was undetermined owing to the lack of quantitative analysis. METHODS: We systematically searched MEDLINE, Cochrane Library, EMBASE, and Web of Science for randomized controlled trials that compared regional analgesia in pediatric inguinal surgeries. After critical study screening and selection, a random-effects network meta-analysis was performed. The primary outcome was the time to the first rescue analgesic after surgery, and the secondary outcomes were the number of patients requiring rescue analgesics after surgery, postoperative pain scores, incidence of postoperative nausea and vomiting, and other adverse events. RESULTS: This network meta-analysis included 69 randomized controlled trials (4636 patients) that compared 10 regional analgesic techniques. Our study revealed that the quadratus lumborum and transversus abdominis plane blocks had the longest time to the first rescue analgesic after pediatric inguinal surgeries, by 7.7 hours (95% confidence interval [CI], 5.0-10.3) and 6.0 hours (95% CI, 3.9-8.2) when compared with the control group, respectively. In the subgroup involving only inguinal hernia repair, the quadratus lumborum block significantly prolonged the time to the first rescue analgesic than all other regional analgesics. In contrast, in the subgroup involving orchidopexies, only the caudal block significantly prolonged the time to the first rescue analgesic when compared with the control group (4.1 hours; 95% CI, 0.7-7.5). Wound infiltration and landmark-based ilioinguinal-iliohypogastric block had relatively poor analgesic effects than other regional analgesics. No serious adverse effects related to the regional analgesic techniques were reported in any of the included studies. CONCLUSIONS: The quadratus lumborum and transversus abdominis plane blocks had the longest time to the first rescue analgesic and the least rescue analgesic requirement for pediatric inguinal surgeries. Specifically, the quadratus lumborum block had the longest analgesic duration in inguinal hernia repair, and the caudal block was found to be the only regional analgesia that extended the time to the first rescue analgesic in pediatric orchidopexy. Most included randomized controlled trials had some concern or a high risk of bias, and future studies should focus on providing high-quality evidence to further clarify the analgesic effects of regional analgesia for pediatric inguinal surgeries.

Complexities of Coexisting Cardiac Amyloidosis and Coronary Artery Disease: A Contemporary Review of Diagnostic and Treatment Approaches.

Cardiac amyloidosis (CA) represents an emerging challenge in cardiovascular medicine, with notable clinical overlaps and diagnostic complexities when coexisting with coronary artery disease (CAD). This integrative review navigates the intricate terrain of CA and CAD, elucidating epidemiology, clinical presentations, and diagnostic considerations. Examining both immunoglobulin light chain amyloidosis (AL) and transthyretin amyloidosis, we underscore their shared demographic associations, diagnostic intricacies, and potential diagnostic confounders with CAD. Notably, we emphasize the impact of CA on epicardial coronary arteries and the consequential implications for coronary microcirculation. Further exploration reveals the connection between CA and acute myocardial infarction, emphasizing early recognition as pivotal. In terms of differential diagnosis, we underscore the significance of clinical symptoms, electrocardiography, echocardiography, cardiac magnetic resonance, and bone scintigraphy. Additionally, we scrutinize the intricate realm of treatment, encompassing medication selection, antithrombotic strategies, and revascularization modalities. Our review addresses the distinctive challenges posed by CA patients' limited tolerance for conventional therapies. This comprehensive synthesis serves as an invaluable resource for clinicians confronting the intricate intersection of CA and CAD. By offering insights into diagnostic refinement and innovative therapeutic avenues, we aim to enhance patient outcomes and quality of life within this complex clinical landscape.

Microcirculatory dysfunction in hypertrophic cardiomyopathy with chest pain assessed by angiography-derived microcirculatory resistance.

Chest pain, a common initial symptom in hypertrophic cardiomyopathy (HCM) patients, is closely linked to myocardial ischemia, despite the absence of significant coronary artery stenosis. This study explored microvascular dysfunction in HCM patients by employing angiography-derived microcirculatory resistance (AMR) as a novel tool for comprehensive assessment. This retrospective analysis included HCM patients with chest pain as the primary symptom and control patients without cardiac hypertrophy during the same period. The AMR was computed through angiography, providing a wire-free and adenosine-free index for evaluating microcirculatory function. Propensity score matching ensured balanced demographics between groups. This study also investigated the correlation between the AMR and clinical outcomes by utilizing echocardiography and follow-up data. After matching, 76 HCM patients and 152 controls were analyzed. While there was no significant difference in the incidence of epicardial coronary stenosis, the AMR of three epicardial coronary arteries was markedly greater in HCM patients. The criterion of an AMR ≥ 250 mmHg*s/m was that 65.7% of HCM patients experienced coronary microvascular dysfunction (CMD). Independent risk factors for CMD included increased left ventricular (LV) wall thickness (OR = 1.209, 95% CI 1.013-1.443, p = 0.036). Furthermore, an AMR_LAD ≥ 250 mmHg*s/m had an increased cumulative risk of the endpoint (log-rank p = 0.023) and was an independent risk factor for the endpoint (HR = 11.64, 95% CI 1.13-120.03, p = 0.039), providing valuable prognostic insights.

Prognosis impact of multiple novel lymphocyte-based inflammatory indices in patients with initially diagnosed coronary artery disease.

BACKGROUND: This study aimed to evaluate six novel lymphocyte-based inflammatory markers (neutrophil-lymphocyte ratio, monocyte-lymphocyte ratio, platelet-lymphocyte ratio [PLR], systemic immune inflammation index [SII], systemic inflammatory response index, and systemic immune inflammation response index [SIIRI]) in patients with newly diagnosed coronary artery disease [CAD]. METHODS: A total of 959 patients newly diagnosed with CAD and underwent diagnostic coronary angiography were enrolled in this study and followed for major adverse cardiovascular events (MACEs), including cardiovascular death, nonfatal myocardial infarction, and nonfatal stroke. The best cutoff value was used to compare the six indicators. Cox risk regression analysis evaluated the relationship between novel lymphocyte-based inflammatory markers and MACEs in newly diagnosed CAD patients. RESULTS: During a mean follow-up period of 33.3 ± 9.9 months, 229 (23.9%) MACEs were identified. Multivariate Cox regression analysis showed that only SIIRI (hazard ratio [HR]: 5.853; 95% confidence interval [CI]: 4.092-8.371; p < .001) and PLR (HR: 1.725; 95% CI: 1.214-2.452; p = .002) were independent predictors of MACEs. Nevertheless, following the adjustment for covariates, only the SIIRI was found to be a significant predictor MACEs and its corresponding specific endpoint occurrences. The predictive ability of the model was improved when six different inflammatory markers were added to the basic model established by traditional risk factors, namely, the C-index increased, and the SIIRI increased most significantly (AUC: 0.778; 95% CI: 0.743-0.812; p < .001). However, among the six novel inflammatory markers, only SIIRI had improved net reclassification improvement (NRI) and integrated discrimination improvement (IDI) (NRI: 0.187; 95% CI: 0.115-0.259, p < .001. IDI: 0.135; 95% CI: 0.111-0.159, p < .001), which was superior to the basic model established by traditional risk factors. CONCLUSIONS: SIIRI is independent predictor of MACEs in newly diagnosed CAD patients. SIIRI was superior to other measures in predicting MACEs. The combination of SIIRI and traditional risk factors can more accurately predict MACEs.

New Electrocardiographic Score for Predicting the Site of Coronary Artery Occlusion in Inferior Wall Acute Myocardial Infarction.

Background: An electrocardiogram (ECG) was used to determine the type of acute myocardial infarction (MI) and locate the culprit vessel. Inferior wall myocardial infarction (IWMI) patients with the right coronary artery (RCA) as the culprit vessel may have a worse clinical prognosis than the left circumflex artery (LCx). We aimed to develop a new, simple, accurate scoring system to localize the RCA. Methods: From January 2018 to January 2020, patients were admitted to the Department of Cardiology of TEDA International Cardiovascular Hospital and the Second Hospital of Tianjin Medical University due to IWMI and coronary angiography confirmed that the infarct-related vessel was a single RCA or LCx. ECG of patients before percutaneous coronary intervention (PCI) was collected to quantitatively analyze the characteristics of ST-segment deviation in non-inferior wall leads (N-IWL) and establish the RCA score in N-IWL. Results: 149 patients were enrolled, including 83 in the RCA group and 66 in the LCx group. Finally, ST-segment depression (ST↓) lead I, aVR, V1, and V6, and ST↓≥ 1mm in lead V4 were found to be associated with the location of the RCA. The sensitivity, specificity, and area under the curve (AUC) of the N-IWL RCA scoring system were 77.1%, 72.7%, and 0.83, respectively. The diagnostic ability of the scoring system was better than that of other algorithms and scoring systems. Conclusion: ECG helps identify the RCA in patients with IWMI before PCI. The N-IWL RCA score may help identify the culprit vessel as the RCA in patients with IWMI.

The Systemic Immune Inflammatory Response Index Can Predict the Clinical Prognosis of Patients with Initially Diagnosed Coronary Artery Disease.

Background: Recently, the systemic immune inflammatory response index (SIIRI), a novel and expanded inflammatory response marker, has been an independent predictor of lesion severity in patients with acute coronary syndrome (ACS). However, its predictive role in patients with initially diagnosed coronary artery disease (CAD) remains to be explored. Patients and Methods: We evaluated 959 patients with CAD undergoing an initial coronary intervention. Each patient had laboratory measurements, including blood cell counts, taken after admission and before interventional treatment. The primary endpoint was major cardiovascular events (MACEs), defined as cardiovascular death, nonfatal myocardial infarction(MI), and nonfatal stroke. The secondary endpoints included MACEs and readmission for congestive heart failure(HF). Results: During a mean follow-up period of 33.3±9.9 months, 229 (23.9%) MACEs were recorded. ROC curve analysis displayed that the best cut-off value of SIIRI for predicting MACEs was 247.17*1018/L2. Kaplan-Meier survival curve analysis showed that the survival rate of the low SIIRI group was higher than that of the high SIIRI group (P<0.001). Compared with the low SIIRI group, the high SIIRI group had a significantly higher risk of MACEs (187 cases (39.53%) vs.42 patients (8.64%), P<0.001). Univariate and multivariate Cox regression analyses displayed that high SIIRI levels were independently associated with the occurrence of MACEs in patients with initially diagnosed CAD undergoing percutaneous coronary intervention (PCI) (adjusted hazard ratio [HR]: 3.808, 95% confidence interval [CI%]: 2.643-5.486, P<0.001). Adding SIIRI to conventional risk factor models improved the predictive value of MACEs. Conclusion: Elevated SIIRI is associated with adverse cardiovascular prognosis in patients with initially diagnosed CAD. SIIRI can be a simple and practical index to identify high-risk patients with CAD after PCI.

The Systemic Inflammation Index Predicts Poor Clinical Prognosis in Patients with Initially Diagnosed Acute Coronary Syndrome Undergoing Primary Coronary Angiography.

Background: Systemic inflammation index (SII: neutrophil count * platelet count/lymphocyte count) is a new inflammatory marker that can reflect the degree of systemic inflammatory response after coronary artery disease (CAD). However, the predictive value of the SII for clinical prognosis in patients with initially diagnosed acute coronary syndrome (ACS) has yet to be thoroughly studied. Patients and Methods: Patients with initially diagnosed ACS who underwent primary coronary angiography in our hospital from January 2019 to April 2021 were included in this study. 757 patients with ACS who underwent primary coronary angiography were enrolled. According to the baseline SII level, the patients were divided into a high SII group and a low SII group. The primary endpoint was major cardiovascular events (MACEs), defined as cardiac death, non-fatal myocardial infarction (MI), and non-fatal stroke. Results: At a median follow-up of 33.9 months, 140 (18.5%) MACEs were recorded. Receiver operating characteristic (ROC) curve analysis showed that SII's best cut-off value for predicting MACEs was 713.9*109/L. Kaplan-Meier survival curve analysis showed that the survival rate of the low SII group was higher than the high SII group (P<0.001). Compared with the low SII group, the risk of MACEs was significantly increased in the high SII group (89 cases (33.3%) vs.51 patients (10.4%), P<0.001). Univariate and multivariate Cox regression analysis manifested that high SII level was independently associated with the occurrence of MACEs in patients with ACS undergoing primary coronary angiography (adjusted hazard ratio [HR]: 2.915, 95% confidence interval (CI%): 1.830-4.641, P<0.001). Adding SII to the conventional risk factor model improved the predictive value of MACEs. Conclusion: This study showed that elevated SII was associated with adverse cardiovascular prognosis in patients with ACS undergoing primary coronary angiography, making SII a valuable predictor of poor prognosis in patients with ACS undergoing primary coronary angiography.

Fascia defect closure versus non-closure in minimal invasive direct inguinal hernia mesh repair: a systematic review and meta-analysis of real-world evidence.

PURPOSE: Laparoscopic and robotic inguinal hernia mesh repair are both common surgical procedures worldwide. Postoperative hernia recurrence and seroma formation are important concerns. In ventral hernia, primary defect closure in laparoscopic surgery reduces the recurrence rate. However, there is no synthetic evidence of direct inguinal hernia defect closure versus non-closure in minimal invasive surgery. Therefore, this study investigated the efficacy of defect closure in patients undergoing minimal invasive direct inguinal hernia mesh repair. METHODS: Eligible studies were identified through a search of PubMed, Embase, Cochrane Library, and CINAHL from their inception until March 2022. Studies examining defect closure in laparoscopic direct inguinal hernia repair were included, and a meta-analysis was performed using the random-effect model. Sensitivity analyses were performed by removing one study at a time. The primary outcomes were hernia recurrence and seroma formation. Acute and chronic postoperative pain, operation time, and length of hospital stay were the secondary outcomes. RESULTS: Five nonrandomized studies and one randomized controlled trial were included. Pooled analysis revealed defect closure might reduce the hernia recurrence rate (risk difference, - 0.02; 95% confidence interval [CI] - 0.04 to - 0.00; p = 0.02). The result of seroma formation (odds ratio, 0.49; 95% CI 0.17-1.46; p = 0.20) showed no significant difference. Moreover, no significant differences were observed in acute postoperative pain, chronic pain, length of hospital stay, and operation time. CONCLUSIONS: Our study indicated defect closure seems to be an option to reduce the direct inguinal hernia recurrence rate. No significant benefits were shown in seroma formation and other secondary outcomes. Our study was mostly based on nonrandomized studies and underestimated the effect of defect closure; thus, further high-quality studies are required to draw definitive conclusions.

Unraveling the interplay between norovirus infection, gut microbiota, and novel antiviral approaches: a comprehensive review.

Norovirus infection is a leading cause of acute gastroenteritis worldwide and can also cause harmful chronic infections in individuals with weakened immune systems. The role of the gut microbiota in the interactions between the host and noroviruses has been extensively studied. While most past studies were conducted in vitro or focused on murine noroviruses, recent research has expanded to human noroviruses using in vivo or ex vivo human intestinal enteroids culture studies. The gut microbiota has been observed to have both promoting and inhibiting effects on human noroviruses. Understanding the interaction between noroviruses and the gut microbiota or probiotics is crucial for studying the pathogenesis of norovirus infection and its potential implications, including probiotics and vaccines for infection control. Recently, several clinical trials of probiotics and norovirus vaccines have also been published. Therefore, in this review, we discuss the current understanding and recent updates on the interactions between noroviruses and gut microbiota, including the impact of norovirus on the microbiota profile, pro-viral and antiviral effects of microbiota on norovirus infection, the use of probiotics for treating norovirus infections, and human norovirus vaccine development.

A High-Reliability 12T SRAM Radiation-Hardened Cell for Aerospace Applications.

The static random-access memory (SRAM) cells used in the high radiation environment of aerospace have become highly vulnerable to single-event effects (SEE). Therefore, a 12T SRAM-hardened circuit (RHB-12T cell) for the soft error recovery is proposed using the radiation hardening design (RHBD) concept. To verify the performance of the RHB-12T, the proposed cell is simulated by the 28 nm CMOS process and compared with other hardened cells (Quatro-10T, WE-Quatro-12T, RHM-12T, RHD-12T, and RSP-14T). The simulation results show that the RHB-12T cell can recover not only from single-event upset caused by their sensitive nodes but also from single-event multi-node upset caused by their storage node pairs. The proposed cell exhibits 1.14×/1.23×/1.06× shorter read delay than Quatro-10T/WE-Quatro-12T/RSP-14T and 1.31×/1.11×/1.18×/1.37× shorter write delay than WE-Quatro-12T/RHM-12T/RHD-12T/RSP-14T. It also shows 1.35×/1.11×/1.04× higher read stability than Quatro-10T/RHM-12T/RHD-12T and 1.12×/1.04×/1.09× higher write ability than RHM-12T/RHD-12T/RSP-14T. All these improvements are achieved at the cost of a slightly larger area and power consumption.

Enhancing estimation of cover crop biomass using field-based high-throughput phenotyping and machine learning models.

Incorporating cover crops into cropping systems offers numerous potential benefits, including the reduction of soil erosion, suppression of weeds, decreased nitrogen requirements for subsequent crops, and increased carbon sequestration. The aboveground biomass (AGB) of cover crops strongly influences their performance in delivering these benefits. Despite the significance of AGB, a comprehensive field-based high-throughput phenotyping study to quantify AGB of multiple cover crops in the U.S. Midwest has not been found. This study presents a two-year field experiment carried out in Eastern Nebraska, USA, to estimate AGB of five different cover crop species [canola (Brassica napus L.), rye (Secale cereale L.), triticale (Triticale × Triticosecale L.), vetch (Vicia sativa L.), and wheat (Triticum aestivum L.)] using high-throughput phenotyping and Machine Learning (ML) models. Destructive AGB sampling was performed three times during each spring season in 2022 and 2023. An array of morphological, spectral, thermal, and environmental features from the sensors were utilized as feature inputs of ML models. Moderately strong linear correlations between AGB and the selected features were observed. Four ML models, namely Random Forests Regression (RFR), Support Vector Regression (SVR), Partial Least Squares Regression (PLSR), and Artificial Neural Network (ANN), were investigated. Among the four models, PLSR achieved the highest Coefficient of Determination (R2) of 0.84 and the lowest Root Mean Squared Error (RMSE) of 892 kg/ha (Normalized RMSE (NRMSE) = 8.87%), indicating that PLSR could be the most appropriate method for estimating AGB of multiple cover crop species. Feature importance analysis ranked spectral features like Normalized Difference Red Edge (NDRE), Solar-induced Fluorescence (SIF), Spectral Reflectance at 485 nm (R485), and Normalized Difference Vegetation Index (NDVI) as top model features using PLSR. When utilizing fewer feature inputs, ANN exhibited better prediction performance compared to other models. Using morphological and spectral parameters as input features alone led to a R2 of 0.80 and 0.77 for AGB prediction using ANN, respectively. This study demonstrated the feasibility of high-throughput phenotyping and ML techniques for accurately estimating AGB of multiple cover crop species. Further enhancement of model performance could be achieved through additional destructive sampling conducted across multiple locations and years.

Corrigendum: Unraveling the interplay between norovirus infection, gut microbiota, and novel antiviral approaches: a comprehensive review.

[This corrects the article DOI: 10.3389/fmicb.2023.1212582.].

Logical Resolving-Based Methodology for Efficient Reliability Analysis.

With the CMOS technology downscaling to the deep nanoscale, the aging effects of devices degrade circuit performance and even lead to functional failure. The stress analysis is critical to evaluate the influence of aging effects on digital circuits. Some related analytical work has recently focused on reliability-aware circuit analysis. Nevertheless, the aging dependence among different devices is not considered, which will induce errors of degradation evaluation in the digital circuit. In order to improve the accuracy of reliability-aware static timing analysis, an improved analytical method is proposed by employing logical resolving. Experimental results show that the proposed method has a better evaluation accuracy of aging path delay than traditional strategies. For aging timing evaluation on aging paths, excessive pessimism can be reduced by employing the proposed method. And, a 378× speedup is achieved while having a 0.56% relative error compared with precise SPICE simulation. Moreover, the circuit performance sacrifice of an aging-aware synthesis flow with the proposed method can be decreased. Due to the high efficiency and high accuracy, the proposed method can meet the speed demands of large-scale digital circuit reliability analysis while achieving transistor simulation accuracy.

Novel cancer treatment paradigm targeting hypoxia-induced factor in conjunction with current therapies to overcome resistance.

Chemotherapy, radiotherapy, targeted therapy, and immunotherapy are established cancer treatment modalities that are widely used due to their demonstrated efficacy against tumors and favorable safety profiles or tolerability. Nevertheless, treatment resistance continues to be one of the most pressing unsolved conundrums in cancer treatment. Hypoxia-inducible factors (HIFs) are a family of transcription factors that regulate cellular responses to hypoxia by activating genes involved in various adaptations, including erythropoiesis, glucose metabolism, angiogenesis, cell proliferation, and apoptosis. Despite this critical function, overexpression of HIFs has been observed in numerous cancers, leading to resistance to therapy and disease progression. In recent years, much effort has been poured into developing innovative cancer treatments that target the HIF pathway. Combining HIF inhibitors with current cancer therapies to increase anti-tumor activity and diminish treatment resistance is one strategy for combating therapeutic resistance. This review focuses on how HIF inhibitors could be applied in conjunction with current cancer treatments, including those now being evaluated in clinical trials, to usher in a new era of cancer therapy.

Comparison of the Efficacy of Single-Injection Regional Analgesia Techniques for Total Abdominal Hysterectomy: A Systematic Review and Network Meta-Analysis.

BACKGROUND: Single-injection regional analgesia techniques can provide effective analgesia for abdominal hysterectomy. However, few randomized controlled trials (RCTs) have directly compared these techniques for total abdominal hysterectomy (TAH), and the best strategy remains unknown. OBJECTIVES: In this network meta-analysis, we compared the analgesic efficacy of single-injection regional analgesia techniques in patients who underwent TAH. STUDY DESIGN: A systematic review and network meta-analysis. METHODS: We searched the PubMed, Embase, Cochrane, and CINAHL databases for relevant trials from inception until April 2022. RCTs that examined single-injection regional analgesia techniques for TAH were included. Random-effects network meta-analyses were performed using the frequentist approach. The primary outcome was 24-hour cumulative morphine equivalent consumption. The secondary outcomes were pain scores, time to first request for rescue analgesia, and rates of postoperative nausea and vomiting (PONV). RESULTS: In total, 36 RCTs were included. Network meta-analyses indicated that the erector spinae plane block provided superior analgesia in terms of reduced morphine consumption, low PONV incidence, and longer time to first analgesia request. Moreover, compared with control (i.e., sham or placebo), the quadratus lumborum block provided superior analgesia in terms of time to first analgesia request and resting pain scores. LIMITATIONS: (1) Few studies have examined single-injection regional analgesia techniques other than the transversus abdominis plane block (TAPB) and wound infiltration, leading to a few indirect effect estimates. (2) Heterogeneity existed due to analgesic type/dose, plane block timing, and injection site. (3) Objective outcomes, such as length of hospital stay, were lacking; most studies only included the patient-reported subjective pain score. CONCLUSION: Single-injection blocks are effective analgesic techniques for TAH. Among them, the erector spinae plane block and quadratus lumborum block seem to have superior effects. Further studies should evaluate techniques other than TAPB and wound infiltration to draw definitive conclusions.

The Human Virome: Viral Metagenomics, Relations with Human Diseases, and Therapeutic Applications.

The human body is colonized by a wide range of microorganisms. The field of viromics has expanded since the first reports on the detection of viruses via metagenomic sequencing in 2002. With the continued development of reference materials and databases, viral metagenomic approaches have been used to explore known components of the virome and discover new viruses from various types of samples. The virome has attracted substantial interest since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Increasing numbers of studies and review articles have documented the diverse virome in various sites in the human body, as well as interactions between the human host and the virome with regard to health and disease. However, there have been few studies of direct causal relationships. Viral metagenomic analyses often lack standard references and are potentially subject to bias. Moreover, most virome-related review articles have focused on the gut virome and did not investigate the roles of the virome in other sites of the body in human disease. This review presents an overview of viral metagenomics, with updates regarding the relations between alterations in the human virome and the pathogenesis of human diseases, recent findings related to COVID-19, and therapeutic applications related to the human virome.