Arthroscopic Resection for Extra-articular Ganglion Cysts of Gastrocnemius Near Vessels.

Extra-articular ganglion cysts arising from the gastrocnemius tendon near popliteal vessels can cause pain and claudication. Open resection of this kind of cyst has been described frequently because the vessels can be well protected with a retractor. However, it's a challenge to remove cysts that are near vessels under arthroscopy, because a retractor cannot be used in arthroscopic surgery. This article will report a method of arthroscopic resection for extra-articular ganglion cysts near popliteal vessels.

Intranasal delivery of phenytoin loaded layered double hydroxide nanoparticles improves therapeutic effect on epileptic seizures.

Improving the efficiency of antiseizure medication entering the brain is the key to reducing its peripheral toxicity. A combination of intranasal administration and nanomedicine presents a practical approach for treating epileptic seizures via bypassing the blood-brain barrier. In this study, phenytoin (PHT) loaded layered double hydroxide nanoparticles (BSA-LDHs-PHT) were fabricated via a coprecipitation - hydrothermal method for epileptic seizure control. In this study, we expound on the preparation method and characterization of BSA-LDHs-PHT. In-vitro drug release experiment shows both rapid and continuous drug release from BSA-LDHs-PHT, which is crucial for acute seizure control and chronic epilepsy therapy. In-vivo biodistribution assays after intranasal administration indicate excellent brain targeting ability of BSA-LDHs. Compared to BSA-Cyanine5.5, BSA-LDHs-Cyanine5.5 were associated with a higher brain/peripheral ratio across all tested time points. Following intranasal delivery with small doses of BSA-LDHs-PHT, the latency of seizures in the pentylenetetrazole-induced mouse models was effectively improved. Collectively, the present study successfully designed and applied BSA-LDHs-PHT as a promising strategy for treating epileptic seizures with an enhanced therapeutic effect.

Reverse electron transfer: Novel anaerobic methanogenesis pathway regulated through exogenous CO2 synergized with biochar.

Acid accumulation and carbon emission are two major challenges in anaerobic digestion. Syntrophic consortia can employ reverse electron transfer (RET) to facilitate thermodynamically unfavorable redox reactions during acetogenesis. However, the potential mechanisms and regulatory methods of RET remain unclear. This study examines the regulatory mechanisms by which exogenous CO2 affects RET and demonstrates that biochar maximizes CO2 solubility at 25.8 mmol/L to enhance effects further. CO2 synergized with biochar significantly increases cumulative methane production and propionate degradation rate. From the bioenergetic perspective, CO2 decreases energy level to a maximum of -87 kJ/mol, strengthening the thermodynamic viability. The underlying mechanism can be attributed to RET promotion, as indicated by increased formate dehydrogenase and enrichment of H2/formate-producing bacteria with their partner Methanospirillum hungatei. Moreover, the 5 % 13CH4 and methane contribution result show that CO2 accomplishes directed methanogenesis. Overall, this investigation riches the roles of CO2 and biochar in AD surrounding RET.

Zero-valent iron enhanced methane production of anaerobic digestion by reinforcing microbial electron bifurcation coupled with direct inter-species electron transfer.

Zero-valent iron (ZVI) can facilitate methanogens of anaerobic digestion (AD). However, the impact of ZVI on the micro-energetic strategies of AD microorganisms remains uncertain. This study aimed to elucidate the development of an energy conservation model involving direct interspecies electron transfer (DIET) and electron bifurcate (EB) by using four types of ZVI. Overall, the ZVI addition resulted in a substantial increase in methane production (1.26 to 2.18 times higher), and the effect of boron (B) doped ZVI was particularly pronounced. The underlying mechanism may be the formation of energy harvest pathway related to DIET. In detail, B-doped ZVI could enhance its interfacial binding to cytochrome c. Decreased polar solvation energy from 20.473 to 1.509 kJ/mol is beneficial for electron transfer, thereby augmenting the flavin-bounded Cytc activity and DIET process. Besides, ZVI-enhanced EB enzyme activity like HdrA2B2C2-MvhAGD could improve the EB process, which can couple with DIET for electron transfer and energy conservation. Energy analysis based on EB-coupled DIET metabolism pathways demonstrated that the ATP saved in this coupled model theoretically line in 0.25 to 0.5 mol ATP/mol substrate. Overall, this study offers valuable insights into microbial energetic strategies pertaining to the utilization of conductive materials, with the target of enhancing methane recovery efficiency from organic waste.

Deep Learning Imaging Reconstruction Algorithm for Carotid Dual Energy CT Angiography: Opportunistic Evaluation of Cervical Intervertebral Discs-A Preliminary Study.

Thus, the aim of this study is to evaluate the performance of deep learning imaging reconstruction (DLIR) algorithm in different image sets derived from carotid dual-energy computed tomography angiography (DECTA) for evaluating cervical intervertebral discs (IVDs) and compare them with those reconstructed using adaptive statistical iterative reconstruction-Veo (ASiR-V). Forty-two patients who underwent carotid DECTA were included in this retrospective analysis. Three types of image sets (70 keV, water-iodine, and water-calcium) were reconstructed using 50% ASiR-V and DLIR at medium and high levels (DLIR-M and DLIR-H). The diagnostic acceptability and conspicuity of IVDs were assessed using a 5-point scale. Hounsfield Units (HU) and water concentration (WC) values of the IVDs; standard deviation (SD); and coefficient of variation (CV) were calculated. Measurement parameters of the 50% ASIR-V, DLIR-M, and DLIR-H groups were compared. The DLIR-H group showed higher scores for diagnostic acceptability and conspicuity, as well as lower SD values for HU and WC than the ASiR-V and DLIR-M groups for the 70 keV and water-iodine image sets (all p < .001). However, there was no significant difference in scores and SD among the three groups for the water-calcium image set (all p > .005). The water-calcium image set showed better diagnostic accuracy for evaluating IVDs compared to the other image sets. The inter-rater agreement using ASiR-V, DLIR-M, and DLIR-H was good for the 70 keV image set, excellent for the water-iodine and water-calcium image sets. DLIR improved the visualization of IVDs in the 70 keV and water-iodine image sets. However, its improvement on color-coded water-calcium image set was limited.

Fat mass and obesity-associated protein (FTO) mediated m6A modification of circFAM192A promoted gastric cancer proliferation by suppressing SLC7A5 decay.

Gastric cancer (GC) is a common malignant tumor worldwide, especially in East Asia, with high incidence and mortality rate. Epigenetic modifications have been reported to participate in the progression of gastric cancer, among which m6A is the most abundant and important chemical modification in RNAs. Fat mass and obesity-associated protein (FTO) is the first identified RNA demethylase but little is known about its role in gastric cancer. In our study, data from TCGA and clinical samples showed that FTO was highly expressed in gastric cancer tissues. Kaplan-Meier plotter suggested that patients with the high level of FTO had a poor prognosis. In vitro and in vivo experiments confirmed the role of FTO in promoting gastric cancer cell proliferation. Mechanistically, we found that FTO bound to circFAM192A at the specific site and removed the m6A modification in circFAM192A, protecting it from degradation. CircFAM192A subsequently interacted with the leucine transporter solute carrier family 7 member 5 (SLC7A5) and enhancing its stability. As a result, an increased amount of SLC7A5 was on the membrane, which facilitated leucine uptake and activated the mTOR signaling pathway. Therefore, our study demonstrated that FTO promoted gastric cancer proliferation through the circFAM192A/SLC7A5 axis in the m6A-dependent manner. Our study shed new light on the role of FTO in gastric cancer progression.

Pregnancy-related knowledge in women with epilepsy in childbearing age: A pilot questionnaire survey from China.

PURPOSE: We aim to understand the knowledge of and attitudes toward pregnancy issues among women with epilepsy (WWE) and their caregivers and analyze the answers from the questionnaire to expose topics that require educational activities; thus, WWE experiences pregnancy better. METHODS: WWE at their childbearing age and/or their caregivers who entered the Fourth Affiliated Hospital of Zhejiang University for treatment of their condition were invited to fill out a questionnaire between March 1 and November 31, 2022. RESULTS: A combined total of 205 WWE and 142 caregivers completed the questionnaires. Among the surveyed WWE, a majority (63.74%) reported experiencing at least one miscarriage or induced abortion. However, a significant proportion (84.62%) of these WWE were still able to successfully give birth to at least one child. Furthermore, the offspring of these WWE showed no significant differences compared to the offspring of women without epilepsy, as reported by 93.51% of the participants. The participants' knowledge regarding the impact of epilepsy on pregnancy was found to be comparable, with average scores of 7.74 and 7.84, respectively. The participants exhibited a limited comprehension of antiseizure medications (ASMs)-related knowledge, specifically pertaining to ASMs adjustment during pregnancy (17.56% vs. 16.90%) and offspring outcomes (30.24% vs. 26.06%). Statistical analysis revealed significant correlations between the overall score and education level (p < .001), as well as epilepsy duration (p = .008). Regarding the source of knowledge, participants acknowledged primarily relying on neurologists, who remained their preferred choice for consultation. CONCLUSION: In our study, the understanding of pregnancy-related knowledge did not differ from WWE and their caregivers, both are far from satisfactory in certain areas. It is urgent for WWE and their caregivers to improve their pregnancy-related knowledge of epilepsy. As their primary access is from knowledgeable health care professionals like neurologists, well-trained neurologists in epilepsy management during pregnancy are in need.

Recognition memory deficits detected through eye-tracking in well-controlled children with self-limited epilepsy with centrotemporal spikes.

OBJECTIVE: Children with self-limited epilepsy characterized by centrotemporal spikes (SeLECTS) exhibit cognitive deficits in memory during the active phase, but there is currently a lack of studies and techniques to assess their memory development after well-controlled seizures. In this study, we employed eye-tracking techniques to investigate visual memory and its association with clinical factors and global intellectual ability, aiming to identify potential risk factors by examining encoding and recognition processes. METHODS: A total of 26 recruited patients diagnosed with SeLECTS who had been seizure-free for at least 2 years, along with 24 control subjects, underwent Wechsler cognitive assessment and an eye-movement-based memory task while video-electroencephalographic (EEG) data were recorded. Fixation and pupil data related to eye movements were utilized to detect distinct memory processes and subsequently to compare the cognitive performance of patients exhibiting different regression patterns on EEG. RESULTS: The findings revealed persistent impairments in visual memory among children with SeLECTS after being well controlled, primarily observed in the recognition stage rather than the encoding phase. Furthermore, the age at onset, frequency of seizures, and interictal epileptiform discharges exhibited significant correlations with eye movement data. SIGNIFICANCE: Children with SeLECTS exhibit persistent recognition memory impairment after being well controlled for the disease. Controlling the frequency of seizures and reducing prolonged epileptiform activity may improve memory cognitive development. The application of the eye-tracking technique may provide novel insights into exploring memory cognition as well as underlying mechanisms associated with pediatric epilepsy.

Phase angle - A screening tool for malnutrition, sarcopenia, and complications in gastric cancer.

BACKGROUND: Patients with gastric cancer (GC) are more likely to experience malnutrition and muscle wasting. This study aims to investigate the potential of phase angle (PhA) as a screening tool for identifying malnutrition and sarcopenia in GC patients, as well as its association with short-term outcomes after radical gastrectomy. METHODS: This cross-sectional study enrolled patients diagnosed with GC at The Affiliated People's Hospital of Jiangsu University from October 2021 to September 2022. PhA was measured using bioelectrical impedance analysis. Computed tomography scan images were analyzed for body composition at the level of the third lumbar vertebra. Malnutrition was diagnosed using Global Leadership Initiative on Malnutrition (GLIM) criteria. Sarcopenia diagnosis was based on the Asian Working Group for Sarcopenia (AWGS) 2019 criteria. RESULTS: A total of 248 patients with GC were analyzed, including 188 patients who underwent radical gastrectomy. Of these, 71.4 % (n = 177) were male and 28.6 % (n = 71) were female and the median overall age was 68 years (IQR: 61-72 years). According to GLIM criteria, 49.2 % (n = 122) of patients were malnourished and 19.8 % (n = 49) had sarcopenia based on AWGS criteria. A one-degree decrease in PhA was significantly associated with GLIM malnutrition (Odds Ratio [OR] = 8.108, 95 % CI:3.181-20.665) and sarcopenia (OR = 2.903, 95 % CI:1.170-7.206). PhA exhibited fair to good diagnostic accuracy in identifying GLIM malnutrition (male: AUC = 0.797; female: AUC = 0.816) and sarcopenia (male: AUC = 0.814; female: AUC = 0.710). Low PhA (OR = 3.632, 95 % CI: 1.686-7.824) and operation time (OR = 2.434, 95 % CI:1.120-5.293) were independently associated with the risk of postoperative complications. CONCLUSIONS: PhA can serve as a reliable screening tool for identifying patients at risk of malnutrition, sarcopenia, and postoperative complications in GC.

Enhancing sustainable crop cultivation: The impact of renewable soil amendments and digestate fertilizer on crop growth and nutrient composition.

Utilizing digestate as a fertilizer enhances soil nutrient content, improves fertility, and minimizes nutrient runoff, mitigating water pollution risks. This alternative approach replaces commercial fertilizers, thereby reducing their environmental impact and lowering greenhouse gas emissions associated with fertilizer production and landfilling. Herein, this study aimed to evaluate the impact of various soil amendments, including carbon fractions from waste materials (biochar, compost, and cocopeat), and food waste anaerobic digestate application methods on tomato plant growth (Solanum lycopersicum) and soil fertility. The results suggested that incorporating soil amendments (biochar, compost, and cocopeat) into the potting mix alongside digestate application significantly enhances crop yields, with increases ranging from 12.8 to 17.3% compared to treatments without digestate. Moreover, the combination of soil-biochar amendment and digestate application suggested notable improvements in nitrogen levels by 20.3% and phosphorus levels by 14%, surpassing the performance of the those without digestate. Microbial analysis revealed that the soil-biochar amendment significantly enhanced biological nitrification processes, leading to higher nitrogen levels compared to soil-compost and soil-cocopeat amendments, suggesting potential nitrogen availability enhancement within the rhizosphere's ecological system. Chlorophyll content analysis suggested a significant 6.91% increase with biochar and digestate inclusion in the soil, compared to the treatments without digestate. These findings underscore the substantial potential of crop cultivation using soil-biochar amendments in conjunction with organic fertilization through food waste anaerobic digestate, establishing a waste-to-food recycling system.

The Role of Thoracic Vertebral Body Dosimetry in Minimizing Acute Hematologic Toxicities of Patients With Non-Small Cell Lung Cancer Receiving Lung Radiation Therapy and Immunotherapy.

PURPOSE: Hematologic toxicities (HTs) are among the most common toxicities of combined immunotherapy and radiation therapy (RT). It remains essential to prevent RT-induced HTs because they can cause treatment discontinuation (influencing antitumoral effects) and because lymphopenia might dampen the effects of immunotherapy. To date, there are no studies examining the effect of thoracic vertebral body (TVB) RT dose on HTs in patients with non-small cell lung cancer receiving combined lung RT and programmed cell death (ligand) 1 immunotherapy. METHODS AND MATERIALS: For standardization, all doses were reported as 2-Gy equivalents (EQD2). Mirroring publications before the immunotherapy era, TVB volumes referred to T1-T10, and specific dosimetric parameters (DmeanEQD2, V5EQD2-V60EQD2) were analyzed. Logistic regression estimated associations between grade ≥3 HTs (HT3+) and dosimetric/clinical parameters. Normal tissue complication probability (NTCP) models were constructed by logistic regression analysis modeling for HT3+. Receiver operating characteristic (ROC) analysis delineated TVB dosimetric thresholds, the stratification of which was able to evaluate post-RT absolute lymphocyte count and immunotherapy responses. Areas under the curve (AUCs) for NTCP models were corroborated by bootstrapping (optimism-corrected) methodology. RESULTS: In 132 patients, there were 26 (19.7%) instances of HT3+. On multivariate analysis, DmeanEQD2 and V5EQD2 to V20EQD2 were associated with HT3+ (P < .05 for all). The NTCP models illustrated a 50% probability of HT3+ at a DmeanEQD2 = 39.8 Gy, V5EQD2 = 87.4%, V10EQD2 = 77.0%, and V20EQD2 = 68.4%. ROC analysis delineated optimal thresholds of HT3+ with DmeanEQD2 ± 30.2 Gy, V5EQD2 ± 69.1%, V10EQD2 ± 64.6%, and V20EQD2 ± 53.5%. Patients treated with values above those cutoffs had over double the risk of HT3+, with significant differences in post-RT absolute lymphocyte count and immunotherapy responses (P < .05 for all). AUCs for each individual parameter ranged from 0.743 to 0.798, and combining all 4 aforementioned cutoffs into a ROC curve resulted in a qualitatively higher AUC (0.836). CONCLUSIONS: This hypothesis-generating work suggests that TVB dosimetry may equate with HT3+ in patients with non-small cell lung cancer undergoing combined lung RT/immunotherapy. Applying TVB dose constraints in this population could reduce HT3+ and avoid dampening of immunotherapy responses, but prospective validation is required.

A fast and non-invasive artificial intelligence olfactory-like system that aids diagnosis of Parkinson's disease.

BACKGROUND AND PURPOSE: Several previous studies have shown that skin sebum analysis can be used to diagnose Parkinson's disease (PD). The aim of this study was to develop a portable artificial intelligence olfactory-like (AIO) system based on gas chromatographic analysis of the volatile organic compounds (VOCs) in patient sebum and explore its application value in the diagnosis of PD. METHODS: The skin VOCs from 121 PD patients and 129 healthy controls were analyzed using the AIO system and three classic machine learning models were established, including the gradient boosting decision tree (GBDT), random forest and extreme gradient boosting, to assist the diagnosis of PD and predict its severity. RESULTS: A 20-s time series of AIO system data were collected from each participant. The VOC peaks at a large number of time points roughly concentrated around 5-12 s were significantly higher in PD subjects. The gradient boosting decision tree model showed the best ability to differentiate PD from healthy controls, yielding a sensitivity of 83.33% and a specificity of 84.00%. However, the system failed to predict PD progression scored by Hoehn-Yahr stage. CONCLUSIONS: This study provides a fast, low-cost and non-invasive method to distinguish PD patients from healthy controls. Furthermore, our study also indicates abnormal sebaceous gland secretion in PD patients, providing new evidence for exploring the pathogenesis of PD.

High HPK1+PD-1+TIM-3+CD8+ T cells infiltration predicts poor prognosis to immunotherapy in NSCLC patients.

At present the efficacy of immune checkpoint inhibitors (ICIs) remains limited. The lack of responsiveness in certain patients may be attributed to CD8+ T cell exhaustion within the tumor microenvironment (TME). Hematopoietic progenitor kinase 1 (HPK1) has been identified as a mediator of T cell dysfunction, leading to our hypothesis that HPK1 positive exhausted CD8+ T cells could serve as a predictor for ICIs' efficacy in NSCLC patients, and potentially indicate key cellular subset causing ICIs resistance. Here, we retrospectively collected tumor tissue samples from 36 NSCLC patients who underwent first-line immunotherapy. Using multiplex immunohistochemistry, we visualized various PD-1+CD8+ T cell subsets and explore biomarkers for response. The analysis endpoints included overall response rate (ORR), progression free survival (PFS), and overall survival (OS), correlating them with levels of cell infiltration or effective density. We found that the proportion of PD-1+CD8+ T cell subsets did not align with predictions for ORR, PFS, and OS. Conversely, a high infiltration of HPK1+PD-1+TIM-3+CD8+ T cells was identified as an independent risk factor for both PFS (P = 0.019) and OS (P = 0.03). These cells were found to express the highest levels of Granzyme B, and the secretion of Granzyme B in CD8+ T cell subsets was related to TCF-1. In conclusion, these data suggest that a high infiltration of HPK1+PD-1+TIM-3+CD8+ T cells correlates with poor clinical outcomes in NSCLC patients receiving immunotherapy. These cells may represent terminally exhausted T cells that fail to respond to ICIs, thereby laying the groundwork for the potential integration of HPK1 inhibitors with immunotherapy to enhance treatment strategy.

Enhanced thermophilic dark fermentation of hydrogen production from food waste by Fe-modified biochar.

The industrialization of hydrogen production through dark fermentation of food waste faces challenges, such as low yields and unpredictable fermentation processes. Biochar has emerged as a promising green additive to enhance hydrogen production in dark fermentation. Our study demonstrated that the introduction of Fe-modified biochar (Fe-L600) significantly boosted hydrogen production during thermophilic dark fermentation of food waste. The addition of Fe-L600 led to a remarkable 31.19% increase in hydrogen yield and shortened the time needed for achieving stabilization of hydrogen production from 18 h to 12 h. The metabolite analysis revealed an enhancement in the butyric acid pathway as the molar ratio of acetic acid to butyric acid decreased from 3.09 to 2.69 but hydrogen yield increased from 57.12 ± 1.48 to 76.78 ± 2.77 mL/g, indicating Fe-L600 improved hydrogen yield by regulating crucial metabolic pathways of hydrogen production. The addition of Fe-L600 also promoted the release of Fe2+ and Fe3+ and increased the concentrations of Fe2+ and Fe3+ in the fermentation system, which might promote the activity of hydrogenase and ferredoxin. Microbial community analysis indicated a substantial increase in the relative abundance of Thermoanaerobacterium after thermophilic dark fermentation. The relative abundances of microorganisms responsible for hydrolysis and acidogenesis were also observed to be improved in the system with Fe-L600 addition. This research provides a feasible strategy for improving hydrogen production of food waste and deepens the understanding of the mechanisms of biochar.

Risk factors for stroke outcomes in adults: Stroke in China.

This study aimed to determine the possible risk factors for stroke outcomes based on prospective cohort study in China. A total of 146 stroke patients were recruited and divided into 2 groups, which assessed using the modified Rankin Scale (mRS), good outcomes (mRS <= 2) and poor outcomes group (mRS > 2). Demographic, clinical, and laboratory characteristics of participants were obtained from the medical record. The multivariable logistic regression analysis was employed to assess the risk factors for stroke outcomes. Of 146 participants, 28 (19.18%) were presented with poor outcomes at day 90. As a result of multivariable logistic regression analysis, a significantly increased risk of stroke outcomes was found in patients with Barthel Index (BI) score (stroke (OR 1.50, 95% CI 1.21 ~ 1.85, P < .001) and IS (OR 1.48, 95% CI 1.20 ~ 1.83, P < .001)).

Multimodal Continual Learning for Process Monitoring: A Novel Weighted Canonical Correlation Analysis With Attention Mechanism.

Aimed at sequential dynamic modes, a novel multimodal weighted canonical correlation analysis using an attention (MWCCA-A) mechanism is introduced to derive a single model for process monitoring, by integrating two ideas of replay and regularization in continual learning. Under the assumption that data are received sequentially, subsets of data from past modes with dynamic features are selected and stored as replay data, which are utilized together with the current mode data for continual model parameter estimation. The weighted canonical correlation analysis (WCCA) is introduced to achieve appropriate weightings of past modes' replay data so that the latent variables are extracted by maximizing the weighted correlation with its prediction via the attention mechanism. Specifically, replay data weightings are obtained via the probability density estimation from each mode. This is also beneficial in overcoming data imbalance among multiple modes and consolidating the significant features of past modes further. Alternatively, the proposed model also regularizes parameters based on its previous modes' importance, which is measured by synaptic intelligence (SI). Meanwhile, the objective is decoupled into a regularization-related part and a replay-related part, to overcome the potentially unstable optimization trajectory of SI-based continual learning. In comparison with several multimode monitoring methods, the effectiveness of the proposed MWCCA-A approach is demonstrated by a continuous stirred tank heater (CSTH), Tennessee Eastman process (TEP), and a practical coal pulverizing system.

Comprehensive analysis of thirteen-gene panel with prognosis value in Multiple Myeloma.

BACKGROUND: Although there are many treatments for Multiple myeloma (MM), patients with MM still unable to escape the recurrence and aggravation of the disease. OBJECTIVE: We constructed a risk model based on genes closely associated with MM prognosis to predict its prognostic value. METHODS: Gene function enrichment and signal pathway enrichment analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, univariate and multivariate Cox regression analysis, Kaplan-Meier (KM) survival analysis and Receiver Operating Characteristic (ROC) analysis were used to identify the prognostic gene signature for MM. Finally, the prognostic gene signature was validated using the Gene Expression Omnibus (GEO) database. RESULTS: Thirteen prognostic genes were screened by univariate Cox analysis and LASSO regression analysis. Multivariate Cox analysis revealed risk score to be an independent prognostic factor for patients with MM [Hazard Ratio (HR) = 2.564, 95% Confidence Interval (CI) = 2.223-2.958, P< 0.001]. The risk score had a high level of predictive value according to ROC analysis, with an area under the curve (AUC) of 0.744. CONCLUSIONS: The potential prognostic signature of thirteen genes were assessed and a risk model was constructed that significantly correlated with prognosis in MM patients.

Life cycle assessment and cost-benefit analysis of small-scale anaerobic digestion system treating food waste onsite under different operational conditions.

This study employed life cycle assessment and cost-benefit analysis to evaluate the environmental and economic profile of a real decentralized small-scale anaerobic digestion (AD) system treating food waste (FW). Different operational conditions, including temperature, biochar addition, biogas engine efficiency, and FW loading, were compared via scenario analysis. Biochar addition could potentially obtain carbon reduction and save fossil fuel. Moreover, at high FW loading and biogas engine efficiency, biochar addition achieved 1-3190% better performance than the system without biochar in all the nine impact categories. The system under mesophilic conditions performed worse than ambient conditions due to high energy demand. All the current scenarios resulted in a monetary loss at US$ 480 k-681 k, while profit was possible if the capital cost and operator salary decreased significantly. Overall, operating the small-scale AD system under ambient temperature with biochar addition was preferred due to its potential environmental benefits and economic profits.

SCCAM: Supervised Contrastive Convolutional Attention Mechanism for Ante-Hoc Interpretable Fault Diagnosis With Limited Fault Samples.

In real industrial processes, fault diagnosis methods are required to learn from limited fault samples since the procedures are mainly under normal conditions and the faults rarely occur. Although attention mechanisms have become increasingly popular for the task of fault diagnosis, the existing attention-based methods are still unsatisfying for the above practical applications. First, pure attention-based architectures like transformers need a substantial quantity of fault samples to offset the lack of inductive biases thus performing poorly under limited fault samples. Moreover, the poor fault classification dilemma further leads to the failure of the existing attention-based methods to identify the root causes. To develop a solution to the aforementioned problems, we innovatively propose a supervised contrastive convolutional attention mechanism (SCCAM) with ante-hoc interpretability, which solves the root cause analysis problem under limited fault samples for the first time. First, accurate classification results are obtained under limited fault samples. More specifically, we integrate the convolutional neural network (CNN) with attention mechanisms to provide strong intrinsic inductive biases of locality and spatial invariance, thereby strengthening the representational power under limited fault samples. In addition, we ulteriorly enhance the classification capability of the SCCAM method under limited fault samples by employing the supervised contrastive learning (SCL) loss. Second, a novel ante-hoc interpretable attention-based architecture is designed to directly obtain the root causes without expert knowledge. The convolutional block attention module (CBAM) is utilized to directly provide feature contributions behind each prediction thus achieving feature-level explanations. The proposed SCCAM method is testified on a continuous stirred tank heater (CSTH) and the Tennessee Eastman (TE) industrial process benchmark. Three common fault diagnosis scenarios are covered, including a balanced scenario for additional verification and two scenarios with limited fault samples (i.e., imbalanced scenario and long-tail scenario). The effectiveness of the presented SCCAM method is evidenced by the comprehensive results that show our method outperforms the state-of-the-art methods in terms of fault classification and root cause analysis.