Clinical characteristics and risk factors for seizures to recur in calcified neurocysticercosis : Prospective cohort Study

AIM

Calcification of degenerating neurocysticercosis (NCC) is common and likely to occur late in the degenerative process and is important for seizure foci. The present study was aimed at identifying the clinical and radiological variables associated with seizure recurrence in people with single or multiple calcified NCC lesions.

MATERIAL AND METHODS

We evaluated 85 adult patients with calcified NCC lesions for recurrence of seizures during the follow-up period of one year.

RESULTS

The mean age of the study population was 24.49 ± 9.17 years. Nocturnal seizures were present in 43.5% and serial seizures in 42.4%. A single calcified lesion was present in 61 (71.8%), and perifocal oedema surrounding the calcified lesions was present in 38 (44.7%). Recurrence of seizures was noted in 37 (43.5%) of the cases. On multivariate analysis, the factors that were significantly associated with the recurrence of seizures were: nocturnal seizures [OR: 0.054 (0.015-0.199)], serial seizures [OR: 0.141 (0.041-0.485)], and perifocal oedema [OR: 0.031 (0.008-0.129)].

CONCLUSION

In our study, serial seizures, nocturnal seizures, and perifocal oedema were linked with the recurrence of seizures in calcified NCC lesions. Perilesional oedema should be treated aggressively with anti-inflammatory/immunosuppressive therapy as well as with anti-seizure medication.

The effect of 5A self-management program on medication adherence of epileptic patients during the COVID - 19 pandemic: A randomized controlled trial

BACKGROUND

Adherence to medication adherence plays a vital role in controlling the problems and complications of epilepsy. During the COVID - 19 pandemic and limitations of face-to-face education, the use of distance education can play an important role in providing education to patients. The aim of this study is the effect of model 5A self-management training on medication adherence in epileptic patients.

METHODS

In this single-blind randomized controlled trial, 56 epileptic patients referred to Shiraz Namazi Hospital were divided into intervention and control groups using random allocation. Thereafter, 5A self - management training sessions were virtually held in 5 sessions in WhatsApp application for intervention group. The data collection tool was MMAS-8 at two stages of before and two months after intervention. Data analysis was performed using SPSS 21 software.

RESULTS

The results of Wilcoxon test showed that in intervention group, the mean drug adherence in patients after intervention significantly increased compared to before intervention (p = 0.005). But in control group, this was not significant (p = 0.909). According to results of Mann-Whitney test, there was no significant difference between intervention and control groups before intervention (p = 0.632). However, by passing two months from intervention, a significant difference was found between intervention and control groups (p = 0.041).

CONCLUSIONS

Based on results, the implementation of model 5A can be effective on medication adherence in epileptic patients. This program can be considered as a suitable method in epileptic patients during COVID - 19 pandemic.

Association between health literacy with stress, anxiety and depression in multiple sclerosis patients: A cross sectional analytical study

OBJECTIVE

Multiple sclerosis is one of the diseases of the central nervous system, which causes numerous physical and mental problems. Since stress, anxiety and depression are effective in various dimensions of chronic diseases management and considering that health literacy plays a decisive role in the quality of life of these patients. Therefore, this study was conducted with the aim of determining the association between health literacy and stress, anxiety and depression.

MATERIALS AND METHODS

The current research is a cross-sectional analytical study that was conducted with the participation of 164 patient's from the MS society of Jahrom city with convenience sampling. The data collection tool was the health literacy questionnaire of multiple sclerosis patients and a 21-question stress, anxiety and depression questionnaire. SPSS - 21 software, descriptive statistics and spearman and chi-square tests were used to analyze the data.

RESULTS

The findings showed that the majority of patients had a borderline health literacy (53.7%). 43.3% of patients had adequate level of health literacy. Also, the findings showed that the stress, anxiety and depression levels of the majority of patients were moderate. Spearman's test showed that there is a negative and significant correlation between health literacy and stress in multiple sclerosis patients (p=0.03) (r=-0.37). While there was no significant correlation between health literacy and anxiety and depression of patients.

CONCLUSION

The findings showed that with the increase in the health literacy, the rate of stress in patient's decreases.

Taste Disorder and Tongue Numbness After Lithium Overdose

PURPOSE

Drug-induced taste disturbances are prevalent in clinical practice, with dysgeusia being a frequent manifestation. This study aims to present a case of taste disorders and tongue numbness induced by a lithium overdose.

CASE REPORT

A 33-year-old woman with bipolar II disorder attempted suicide by ingesting multiple drugs, including lithium and benzodiazepines. She exhibited weakness but was conscious after admission. Laboratory analyses indicated elevated serum lithium and urine benzodiazepine levels. Admitted to a psychiatric ward, her symptoms included diarrhea, poor appetite, and postprandial nausea. Two weeks later, she reported altered taste sensations and tongue numbness following the overdose. Her ongoing medication included venlafaxine, valproate sodium, and clozapine. Symptoms improved over time without specific treatment, aligning with increased appetite and weight gain.

CONCLUSION

Drug-induced taste disturbances have a substantial impact on patients' quality of life and medication adherence. This case brings attention to taste disorders induced by lithium and suggests potential mechanisms that could contribute to taste alterations. It underscores the importance of conducting thorough assessments in patients experiencing gustatory symptoms, particularly during the ongoing pandemic.

Challenges in The Diagnosis of Ischemic stroke, Tuberculous Meningitis, and Co-Infection with HIV in a Socially Isolated Elderly Patient

BACKGROUND

Ischemic stroke has been a common cause of death and disability in Taiwan, particularly among the elderly. Social isolation is a significant issue in an aging society, which can be associated with delayed medical care and difficulties in diagnosis.

CASE

A 76-year-old man presented with altered mental status, left-sided weakness, and declining cognitive function over three months. He had limited social connections and an unknown medical history. Initial brain imaging showed communicating hydrocephalus. Cerebrospinal fluid analysis revealed increased lymphocytes and high protein levels. Further imaging revealed multiple hyperintense lesions in the brain's white matter and acute ischemic stroke in specific areas. The patient was diagnosed with tuberculosis and HIV coinfection, leading to probable tuberculous meningitis, HIV encephalopathy, and pneumocystis jirovecii pneumonia. Treatment with antituberculous agents, antibiotics, and steroids improved the patient's level of consciousness.

CONCLUSION

Addressing social isolation and altered consciousness in elderly individuals requires a thoughtful approach. Reconsidering the differential diagnosis is crucial when it doesn't match the clinical severity. Clinicians should consider rare co-occurrences like ischemic stroke, TBM, and HIV infection in atypical TBM cases. A biopsychosocial perspective helps gather a comprehensive medical history for holistic care. Early diagnosis and timely intervention are vital for better outcomes in severe infections.

Perception of Neurologists on Intraoperative Neurophysiological Monitoring in Saudi Arabia

OBJECTIVE

Intraoperative neurophysiological monitoring (IONM) has the advantage of minimizing intraoperative neurological injury and limiting serious postoperative complications. No previous studies have evaluated the importance of IONM, especially in Gulf and Arab countries. We aimed to investigate the importance of IONM, as evaluated from a neurologist perspective in Saudi Arabia.

METHODS

This cross-sectional study was conducted in Saudi Arabia through face-to-face interviews. The inclusion criterion was adult neurology consultants in Saudi Arabia. The instrument used was a self-administered questionnaire consisting of 20 items to evaluate the perceptions on IONM. Data collection was from January 2022 to June 2022.

RESULTS

A total of 72 neurology consultants from Saudi Arabia participated in this study. The years of experience of the participants were 10-20 years (43.1%), most of whom worked in a tertiary healthcare center (72.2%), 31.9% had a certified neurologist trained in IONM, and approximately two-thirds of the institutions did not have an IONM setup (59.7%). Most neurologists believed that IONM should be part of neurology training programs (59.7%). Approximately, half of the respondents believed that IONM was mandatory (52.8%).

CONCLUSION

IONM is considered the standard of care in many complex intracranial, spinal, and vascular surgeries. In our study, the perception of neurologists regarding IONM was promising, and the readiness of secondary and tertiary care centers to implement IONM was encouraging. Education, training, implementation, and regulations regarding IONM should be mandatory to prevent operative complications.

Viewpoint-invariant exercise repetition counting

Counting the repetition of human exercise and physical rehabilitation is common in rehabilitation and exercise training. The existing vision-based repetition counting methods less emphasize the concurrent motions in the same video, and counting skeleton in different view angles. This work analyzed the spectrogram of the pose estimation cosine similarity to count the repetition. Besides the public datasets. This work also collected exercise videos from 11 adults to verify that the proposed method can handle concurrent motion and different view angles. The presented method was validated on the University of Idaho Physical Rehabilitation Movements Data Set (UI-PRMD) and MM-fit dataset. The overall mean absolute error (MAE) for MM-fit was 0.06 with off-by-one Accuracy (OBOA) of 0.94. As for the UI-PRMD dataset, MAE was 0.06 with OBOA 0.95. We have also tested the performance in various camera locations and concurrent motions with 57 skeleton time-series videos with an overall MAE of 0.07 and OBOA of 0.91. The proposed method provides a view-angle and motion agnostic concurrent motion counting. This method can potentially use in large-scale remote rehabilitation and exercise training with only one camera.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13755-023-00258-3.

Deep-kidney: an effective deep learning framework for chronic kidney disease prediction

Chronic kidney disease (CKD) is one of today's most serious illnesses. Because this disease usually does not manifest itself until the kidney is severely damaged, early detection saves many people's lives. Therefore, the contribution of the current paper is proposing three predictive models to predict CKD possible occurrence within 6 or 12 months before disease existence namely; convolutional neural network (CNN), long short-term memory (LSTM) model, and deep ensemble model. The deep ensemble model fuses three base deep learning classifiers (CNN, LSTM, and LSTM-BLSTM) using majority voting technique. To evaluate the performance of the proposed models, several experiments were conducted on two different public datasets. Among the predictive models and the reached results, the deep ensemble model is superior to all the other models, with an accuracy of 0.993 and 0.992 for the 6-month data and 12-month data predictions, respectively.

Zingiberis rhizoma-based carbon dots alter serum oestradiol and follicle-stimulating hormone levels in female mice

Chinese herbs contain substances that regulate female hormones. Our study confirmed that Zingiberis rhizoma carbonisata contains Zingiberis rhizoma-based carbon dots (ZR-CDs), which exert regulatory effects on serum oestradiol and FSH in mice and show impacts on endometrial growth and follicular development that potentially affect the ability of female fertility. ZR-CDs were characterized to clarify the microstructure, optical features, and functional group characteristics. It shows that ZR-CDs are spherical carbon nanostructures ranging from 0.97 to 2.3 nm in diameter, with fluorescent properties and a surface rich in functional groups. We further investigated the impact of ZR-CDs on oestradiol and FSH in serum, growth, and the development of ovarian and uterine using normal female mice and exogenous oestradiol intervention model. It was observed that ZR-CDs accelerated oestrogen metabolism and attenuated oestradiol-induced endometrial hyperplasia. Simultaneously, ZR-CDs triggered an increase in FSH, even in the presence of high-serum oestradiol that inhibits FSH secretion. Our findings suggest that ZR-CDs could be a potential therapeutic treatment for anovulatory menstruation.

Cardiac murmur grading and risk analysis of cardiac diseases based on adaptable heterogeneous-modality multi-task learning

Cardiovascular disease (CVDs) has become one of the leading causes of death, posing a significant threat to human life. The development of reliable Artificial Intelligence (AI) assisted diagnosis algorithms for cardiac sounds is of great significance for early detection and treatment of CVDs. However, there is scarce research in this field. Existing research mainly faces three major challenges: (1) They mainly limited to murmur classification and cannot achieve murmur grading, but attempting both classification and grading may lead to negative effects between different multi-tasks. (2) They mostly pay attention to unstructured cardiac sound modality and do not consider the structured demographic modality, as it is difficult to balance the influence of heterogeneous modalities. (3) Deep learning methods lack interpretability, which makes it challenging to apply them clinically. To tackle these challenges, we propose a method for cardiac murmur grading and cardiac risk analysis based on heterogeneous modality adaptive multi-task learning. Specifically, a Hierarchical Multi-Task learning-based cardiac murmur detection and grading method (HMT) is proposed to prevent negative interference between different tasks. In addition, a cardiac risk analysis method based on Heterogeneous Multi-modal feature impact Adaptation (HMA) is also proposed, which transforms unstructured modality into structured modality representation, and utilizes an adaptive mode weight learning mechanism to balance the impact between unstructured modality and structured modality, thus enhancing the performance of cardiac risk prediction. Finally, we propose a multi-task interpretability learning module that incorporates an important evaluation using random masks. This module utilizes SHAP graphs to visualize crucial murmur segments in cardiac sound and employs a multi-factor risk decoupling model based on nomograms. And then we gain insights into the cardiac disease risk in both pre-decoupled multi-modality and post-decoupled single-modality scenarios, thus providing a solid foundation for AI assisted cardiac murmur grading and risk analysis. Experimental results on a large real-world CirCor DigiScope PCG dataset demonstrate that the proposed method outperforms the state-of-the-art (SOTA) method in murmur detection, grading, and cardiac risk analysis, while also providing valuable diagnostic evidence.

WGBS of embryonic gonads revealed that long non-coding RNAs in the MHM region might be involved in cell autonomous sex identity and female gonadal development in chickens

DNA methylation plays a key role in sex determination and differentiation in vertebrates. However, there are few studies on DNA methylation involved in chicken gonad development, and most focused on male hypermethylated regions (MHM). It is unclear whether there are specific differentially methylated regions (DMRs) in chicken embryonic gonads regulating sex determination and differentiation. Here, the DNA methylation maps showed that the difference of DNA methylation level between sexes was much higher at embryonic day 10 (E10) than that at embryonic day 6 (E6), and the significant differentially methylated regions at both stages were mainly distributed on the Z chromosome, including MHM1 and MHM2. The results of bisulphite sequencing PCR (BSP) and qRT-PCR showed hypomethylation of female MHM and upregulation of long non-coding RNAs (lncRNAs) whose promoter in the MHM region was consistent with the sequencing results, and similar results were in brain and muscle. In female sex-reversed gonads, the methylation pattern of MHM remained unchanged, and the expression levels of the three candidate lncRNAs were significantly decreased compared with those in females, but were significantly increased compared to males. The fluorescence in situ hybridization (FISH) results also showed that these lncRNAs were highly expressed in female embryonic gonads. The results of methyltransferase inhibitor and dual-luciferase reporter assay suggest that lncRNA expression may be regulated by DNA methylation within their promoters. Therefore, we speculated that MHM may be involved in cell-autonomous sex identity in chickens, and that lncRNAs regulated by MHM may be involved in female sexual differentiation.

Ojeok-san enhances platinum sensitivity in ovarian cancer by regulating adipocyte paracrine IGF1 secretion

BACKGROUND

Platinum is a commonly used drug for ovarian cancer (OvCa) treatment, but drug resistance limits its clinical application. This study intended to delineate the effects of adipocytes on platinum resistance in OvCa.

METHODS

OvCa cells were maintained in the adipocyte-conditioned medium. Cell viability and apoptosis were detected by CCK-8 and flow cytometry, separately. Proliferation and apoptosis-related protein expression were assayed by western blot. The IC50 values of cisplatin and carboplatin were determined using CCK-8. IGF1 secretion and expression were assayed via ELISA and western blot, respectively. A xenograft model was established, and pathological changes were detected by H&E staining. Proliferation and apoptosis-associated protein expression was assessed via IHC.

RESULTS

Adipocytes promoted the viability and repressed cell apoptosis in OvCa, as well as enhancing platinum resistance, while the addition of IGF-1 R inhibitor reversed the effects of adipocytes on proliferation, apoptosis, and drug resistance of OvCa cells. Treatment with different concentrations of Ojeok-san (OJS) inhibited the adipocyte-induced platinum resistance in OvCa cells by suppressing IGF1. The combined treatment of OJS and cisplatin significantly inhibited tumour growth in vivo with good mouse tolerance.

CONCLUSION

In summary, OJS inhibited OvCa proliferation and platinum resistance by suppressing adipocyte paracrine IGF1 secretion.

Dry eye disease caused by viral infection: Past, present and future

Following viral infection, the innate immune system senses viral products, such as viral nucleic acids, to activate innate defence pathways, leading to inflammation and apoptosis, control of cell proliferation, and consequently, threat to the whole body. The ocular surface is exposed to the external environment and extremely vulnerable to viral infection. Several studies have revealed that viral infection can induce inflammation of the ocular surface and reduce tear secretion of the lacrimal gland (LG), consequently triggering ocular morphological and functional changes and resulting in dry eye disease (DED). Understanding the mechanisms of DED caused by viral infection and its potential therapeutic strategies are crucial for clinical interventional advances in DED. This review summarizes the roles of viral infection in the pathogenesis of DED, applicable diagnostic and therapeutic strategies, and potential regions of future studies.

HBOC alleviated tumour hypoxia during radiotherapy more intensely in large solid tumours than regular ones

Radiotherapy (RT) is a highly valuable method in cancer therapy, but its therapeutic efficacy is limited by its side effects and tumour radiation resistance. The resistance is mainly induced by hypoxia in the tumour microenvironment (TME). As a nano-oxygen carrier, Haemoglobin-based oxygen carriers (HBOCs) administration is a promising strategy to alleviate tumour hypoxia which may remodel TME to ameliorate radiation resistance and enable RT more effective. In this study, we administered fractionated RT combined with HBOC to treat Miapaca-2 cell and Hela cell xenografts on nude mice. The study found that HBOC relieved hypoxic environment and down-regulate expression of hypoxia-inducible factor-1α (Hif-1α) both in regular (100 mm3) and large (360/400 mm3) tumours. The proliferation and metastasis of tumour tissue also decreased after HBOC application. Nevertheless, in vivo RT combined with HBOC performed more effectively to suppress tumour growth in large tumours than in regular tumours. This is due to more severe hypoxic regions exist in the large solid tumours compared to the regular counterparts, and HBOC administration may be more effective in alleviating hypoxia in large tumours. Thus, HBOC sensitization therapy is more suitable for large solid tumours.

A structural atlas of druggable sites on Nav channels

Voltage-gated sodium (Nav) channels govern membrane excitability by initiating and propagating action potentials. Consistent with their physiological significance, dysfunction, or mutations in these channels are associated with various channelopathies. Nav channels are thereby major targets for various clinical and investigational drugs. In addition, a large number of natural toxins, both small molecules and peptides, can bind to Nav channels and modulate their functions. Technological breakthrough in cryo-electron microscopy (cryo-EM) has enabled the determination of high-resolution structures of eukaryotic and eventually human Nav channels, alone or in complex with auxiliary subunits, toxins, and drugs. These studies have not only advanced our comprehension of channel architecture and working mechanisms but also afforded unprecedented clarity to the molecular basis for the binding and mechanism of action (MOA) of prototypical drugs and toxins. In this review, we will provide an overview of the recent advances in structural pharmacology of Nav channels, encompassing the structural map for ligand binding on Nav channels. These findings have established a vital groundwork for future drug development.

Inhibitory effects of Curcumae Radix carbonisata-based carbon dots against liver fibrosis induced by carbon tetrachloride in mice

As a processed product of traditional Chinese medicine Curcumae Radix, Curcumae Radix Carbonisata (CRC) has been widely used in the treatment of liver diseases in ancient medical books. In this study, novel carbon dots (CDs) extending from 1.0 to 4.5 nm were separated from fluid extricates of CRC. Meanwhile, a liver fibrosis model induced by carbon tetrachloride (CCl4) was utilized to determine the inhibitory effects of CRC-CDs against liver fibrosis. The results exhibited the CRC-CDs with a quantum yield of 1.34% have a significant inhibitory effect on CCl4-induced liver fibrosis, as demonstrated by improving hepatocyte degeneration and necrosis, inflammatory cell infiltration and fibrotic tissue hyperplasia, downregulating the levels of alanine transaminase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), direct bilirubin (DBIL), total bile acid (TBA), triglyceride (TG), tumour necrosis factor-α (TNF-α), interleukin (IL)-6 and IL-1β in the serum, upregulating the contents of superoxide dismutase (SOD), reduced glutathione (GSH), and downregulating the concentration of malondialdehyde (MDA), which lays an important foundation for the development of CRC-CDs as a novel drug for the treatment of liver fibrosis, and provide a certain experimental basis for the clinical application of CRC-CDs in the future.

The host protein CALCOCO2 interacts with bovine viral diarrhoea virus Npro, inhibiting type I interferon production and thereby promoting viral replication

Bovine viral diarrhoea-mucosal disease caused by bovine viral diarrhoea virus (BVDV) is a major infectious disease that affects the cattle industry. The nonstructural protein Npro of BVDV antagonizes the type I interferon (IFN-I) pathway, thereby escaping the host immune response. The exact mechanism by which Npro uses host proteins to inhibit IFN-I production is unclear. The host protein CALCOCO2 was identified as a binding partner of Npro using a yeast two-hybrid screen. The interaction between Npro and CALCOCO2 was confirmed by yeast co-transformation, co-immunoprecipitation assays, and GST pull-down assays. The stable overexpression of CALCOCO2 markedly promoted BVDV propagation, while the knockdown of CALCOCO2 significantly inhibited BVDV replication in MDBK cells. Interestingly, CALCOCO2 inhibited IFN-I and IFN-stimulated gene production in BVDV-infected cells. Ectopic expression of CALCOCO2 effectively reduced IRF3 protein levels via the proteasome pathway. CALCOCO2 was found to promote Npro-mediated ubiquitination degradation of IRF3 by interacting with IRF3. Our results demonstrate the molecular mechanism by which Npro recruits the CALCOCO2 protein to regulate IRF3 degradation to inhibit IFN-I production.

Treatment of Intracranial Hemorrhage Induced Hemichorea- Hemiballism by Low-Frequency Repetitive Transcranial Magnetic Stimulation

An 80-year-old woman with a history of rheumatoid arthritis, hypertension, and hyperlipidemia, and no family history of hyperkinesis developed suddenly involuntary movement and visited our hospital two-day after onset. Neuro-examination revealed hemichorea-hemiballismus in the right side of the body, including the face (Suppl. video). Blood tests revealed neither hyperglycemia nor acanthocyte. Brain MRI showed acute microbleeding in the left subthalamic nucleus (Figure 1A-C). Although she was treated with haloperidol (max. 4.5 mg/day), hemichorea-hemiballismus did not subside. Repetitive transcranial magnetic stimulation (rTMS) with a low-frequency protocol (LFP) (1 Hz, 1200 pulses, with a stimulus intensity of 90% of the resting motor threshold, 3 days/week for 2-week) was applied to the left precentral knob (Figure 1D). Its effect was drastic, as the symptoms disappeared for half-hour after rTMS. Hemichorea-hemiballism then reappeared but was attenuated by repeated rTMS. The symptoms disappeared after one-month. Subthalamic nucleus lesions can develop hemichorea-hemiballism (1). According to a study on Huntington's disease and diabetic hemichorea-hemiballism, increased thalamocortical drive may increase the excitability of excitatory and inhibitory circuits of the frontal cortex as the etiologies of hyperkinesia (2-3). However, the target points of rTMS in treating hemichorea-hemiballism have not been consistent in literature. Moreover, rTMS with a LFP on the bilateral supplementary motor areas is effective in treating chorea in Huntington's disease (2). Additionally, rTMS on the ipsilateral precentral knob (primary motor cortex) with continuous θ burst stimulation (cTBS), which decreases the excitability and inhibitory cortical circuits, was effective in treating contralateral hemichorea caused by midbrain hemorrhage (3). Similar to cTBS, LFP can suppress cortical excitation (4); therefore, we applied rTMS with LFP on the primary motor cortex to treat hemichorea-hemiballism. Our results were drastic for both short- and long-term efficiency. This is the first report of the efficacy of rTMS with LFP in treating hemichorea-hemiballism caused by encephalorrhagia.

Data-driven interpretable analysis for polysaccharide yield prediction

Cornstalks show promise as a raw material for polysaccharide production through xylanase. Rapid and accurate prediction of polysaccharide yield can facilitate process optimization, eliminating the need for extensive experimentation in actual production to refine reaction conditions, thereby saving time and costs. However, the intricate interplay of enzymatic factors poses challenges in predicting and optimizing polysaccharide yield accurately. Here, we introduce an innovative data-driven approach leveraging multiple artificial intelligence techniques to enhance polysaccharide production. We propose a machine learning framework to identify highly accurate polysaccharide yield prediction modeling methods and uncover optimal enzymatic parameter combinations. Notably, Random Forest (RF) and eXtreme Gradient Boost (XGB) demonstrate robust performance, achieving prediction accuracies of 93.0% and 95.6%, respectively, while an independently developed deep neural network (DNN) model achieves 91.1% accuracy. A feature importance analysis of XGB reveals the enzyme solution volume's dominant role (43.7%), followed by time (20.7%), substrate concentration (15%), temperature (15%), and pH (5.6%). Further interpretability analysis unveils complex parameter interactions and potential optimization strategies. This data-driven approach, incorporating machine learning, deep learning, and interpretable analysis, offers a viable pathway for polysaccharide yield prediction and the potential recovery of various agricultural residues.

Cost dynamics of onshore wind energy in the context of China's carbon neutrality target

Wind energy has become one of the most important measures for China to achieve its carbon neutrality goal. The spatial and temporal evolvement of economic competitiveness for wind energy becomes an important concern in shaping the decarbonization pathway in China. There has been an urgent need in power system planning to model the future dynamics of cost decline and supply potential for wind power in the context of carbon neutrality until 2060. Existing studies often fail to capture the rapid decline in the cost of wind power generation in recent years, and the prediction of wind power cost decline is more conservative than the reality. This study constructs an integrated model to evaluate the cost-competitiveness and grid parity potential of China's onshore wind electricity at fine spatial resolution with updated parameters. Results indicate that the total onshore wind potential amounts to 54.0 PWh. The average levelized cost of wind power is expected to decline from CNY 0.39 kWh-1 in 2020 to CNY 0.30 and CNY 0.21 kWh-1 in 2030 and 2060. 28.3%, 67.6%, and 97.6% of the technical potentials hold power costs lower than coal power in 2020, 2030, and 2060.

Salinity causes differences in stratigraphic methane sources and sinks

Methane metabolism, driven by methanogenic and methanotrophic microorganisms, plays a pivotal role in the carbon cycle. As seawater intrusion and soil salinization rise due to global environmental shifts, understanding how salinity affects methane emissions, especially in deep strata, becomes imperative. Yet, insights into stratigraphic methane release under varying salinity conditions remain sparse. Here we investigate the effects of salinity on methane metabolism across terrestrial and coastal strata (15-40 m depth) through in situ and microcosm simulation studies. Coastal strata, exhibiting a salinity level five times greater than terrestrial strata, manifested a 12.05% decrease in total methane production, but a staggering 687.34% surge in methane oxidation, culminating in 146.31% diminished methane emissions. Salinity emerged as a significant factor shaping the methane-metabolizing microbial community's dynamics, impacting the methanogenic archaeal, methanotrophic archaeal, and methanotrophic bacterial communities by 16.53%, 27.25%, and 22.94%, respectively. Furthermore, microbial interactions influenced strata system methane metabolism. Metabolic pathway analyses suggested Atribacteria JS1's potential role in organic matter decomposition, facilitating methane production via Methanofastidiosales. This study thus offers a comprehensive lens to comprehend stratigraphic methane emission dynamics and the overarching factors modulating them.

Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review

The recent advancements made in the realms of Artificial Intelligence (AI) and Artificial Intelligence of Things (AIoT) have unveiled transformative prospects and opportunities to enhance and optimize the environmental performance and efficiency of smart cities. These strides have, in turn, impacted smart eco-cities, catalyzing ongoing improvements and driving solutions to address complex environmental challenges. This aligns with the visionary concept of smarter eco-cities, an emerging paradigm of urbanism characterized by the seamless integration of advanced technologies and environmental strategies. However, there remains a significant gap in thoroughly understanding this new paradigm and the intricate spectrum of its multifaceted underlying dimensions. To bridge this gap, this study provides a comprehensive systematic review of the burgeoning landscape of smarter eco-cities and their leading-edge AI and AIoT solutions for environmental sustainability. To ensure thoroughness, the study employs a unified evidence synthesis framework integrating aggregative, configurative, and narrative synthesis approaches. At the core of this study lie these subsequent research inquiries: What are the foundational underpinnings of emerging smarter eco-cities, and how do they intricately interrelate, particularly urbanism paradigms, environmental solutions, and data-driven technologies? What are the key drivers and enablers propelling the materialization of smarter eco-cities? What are the primary AI and AIoT solutions that can be harnessed in the development of smarter eco-cities? In what ways do AI and AIoT technologies contribute to fostering environmental sustainability practices, and what potential benefits and opportunities do they offer for smarter eco-cities? What challenges and barriers arise in the implementation of AI and AIoT solutions for the development of smarter eco-cities? The findings significantly deepen and broaden our understanding of both the significant potential of AI and AIoT technologies to enhance sustainable urban development practices, as well as the formidable nature of the challenges they pose. Beyond theoretical enrichment, these findings offer invaluable insights and new perspectives poised to empower policymakers, practitioners, and researchers to advance the integration of eco-urbanism and AI- and AIoT-driven urbanism. Through an insightful exploration of the contemporary urban landscape and the identification of successfully applied AI and AIoT solutions, stakeholders gain the necessary groundwork for making well-informed decisions, implementing effective strategies, and designing policies that prioritize environmental well-being.

Knowledge-guided machine learning reveals pivotal drivers for gas-to-particle conversion of atmospheric nitrate

Particulate nitrate, a key component of fine particles, forms through the intricate gas-to-particle conversion process. This process is regulated by the gas-to-particle conversion coefficient of nitrate (ε(NO3-)). The mechanism between ε(NO3-) and its drivers is highly complex and nonlinear, and can be characterized by machine learning methods. However, conventional machine learning often yields results that lack clear physical meaning and may even contradict established physical/chemical mechanisms due to the influence of ambient factors. It urgently needs an alternative approach that possesses transparent physical interpretations and provides deeper insights into the impact of ε(NO3-). Here we introduce a supervised machine learning approach-the multilevel nested random forest guided by theory approaches. Our approach robustly identifies NH4+, SO42-, and temperature as pivotal drivers for ε(NO3-). Notably, substantial disparities exist between the outcomes of traditional random forest analysis and the anticipated actual results. Furthermore, our approach underscores the significance of NH4+ during both daytime (30%) and nighttime (40%) periods, while appropriately downplaying the influence of some less relevant drivers in comparison to conventional random forest analysis. This research underscores the transformative potential of integrating domain knowledge with machine learning in atmospheric studies.

Developmental impacts and toxicological hallmarks of silver nanoparticles across diverse biological models

Silver nanoparticles (AgNPs), revered for their antimicrobial prowess, have become ubiquitous in a range of products, from biomedical equipment to food packaging. However, amidst their rising popularity, concerns loom over their possible detrimental effects on fetal development and subsequent adult life. This review delves into the developmental toxicity of AgNPs across diverse models, from aquatic species like zebrafish and catfish to mammalian rodents and in vitro embryonic stem cells. Our focus encompasses the fate of AgNPs in different contexts, elucidating associated hazardous results such as embryotoxicity and adverse pregnancy outcomes. Furthermore, we scrutinize the enduring adverse impacts on offspring, spanning impaired neurobehavior function, reproductive disorders, cardiopulmonary lesions, and hepatotoxicity. Key hallmarks of developmental harm are identified, encompassing redox imbalances, inflammatory cascades, DNA damage, and mitochondrial stress. Notably, we explore potential explanations, linking immunoregulatory dysfunction and disrupted epigenetic modifications to AgNPs-induced developmental failures. Despite substantial progress, our understanding of the developmental risks posed by AgNPs remains incomplete, underscoring the urgency of further research in this critical area.

Retrograde transgastric jejunostomy for nutritional management and aspiration prevention in cases with severe malignant esophageal strictures

Locally advanced esophageal cancer often presents with dysphagia and can be complicated by aspiration pneumonia. Therefore, nutritional management is important to prevent pneumonia. Enteral nutrition via gastrostomies is common in esophageal cancer patients. Here, we describe the efficacy of nutritional management using a gastrojejunostomy tube retrogradely inserted in the esophagus through gastrostomy to simultaneously drain accumulated fluid on the proximal side of a malignant stricture. We performed this procedure for two cases with severe malignant strictures using two types of endoscope insertion. A 57-year-old male patient (Case 1) underwent a retrograde insertion of a gastrojejunostomy tube for severe esophageal malignant stricture with severe nausea and salivary reflux. After a narrow endoscope was inserted through the gastrostomy fistula, a gastrojejunostomy tube was inserted alongside a guidewire allowing the patient to undergo definitive chemoradiotherapy without symptoms. An 82-year-old male patient (Case 2) was scheduled for a minimally invasive esophagectomy following neoadjuvant chemotherapy after gastrostomy. However, the patient developed aspiration pneumonia due to salivary reflux; before surgery, a narrow nasal endoscope was inserted and passed through the strictures. The percutaneous endoscopic transgastric jejunostomy catheter was retrogradely inserted alongside the guidewire. In patients with malignant strictures and salivary reflux, retrograde insertion of gastrojejunostomy tubes can simultaneously provide enteral nutrition and saliva drainage.

A case of intestinal T-cell lymphoma, not otherwise specified, that showed characteristic findings by magnified endoscopy combined with narrow-band imaging

T-cell lymphoma in the gastrointestinal tract (intestinal T-cell lymphoma, [ITCL]) is rare. ITCL, not otherwise specified (ITCL, NOS) which is a type of ITCL is particularly rare. There are few case reports of ITCL, NOS but no previous reports describe its endoscopic features. In this report, the 69-year-old man was diagnosed with ITCL, NOS. Colonoscopy revealed the elevated legion and edematous mucosa with focal depressions in the lower rectum. On the depressed legions, magnifying endoscopy combined with narrow-band imaging detected the disappearance of glandular structure and branching abnormal blood vessels like a tree. These findings were similar to the tree-like appearance, which has been described as a unique feature of gastric mucosal-associated lymphoid tissue lymphoma. The targeted biopsy of the tree-like appearance showed abnormal histopathological findings which fit the definition of ITCL, NOS. He was treated with chemotherapy and achieved complete remission. As is the case of gastric mucosal-associated lymphoid tissue lymphoma, the tree-like appearance is possibly the unique sign of ITCL, NOS. We report the endoscopic features of ITCL, NOS and show characteristic findings by magnifying endoscopy combined with narrow-band imaging.