A novel CACNA1S gene variant in a child with hypokalemic periodic paralysis: a case report and literature review.

BACKGROUND: The CACNA1S gene encodes the alpha 1 S-subunit of the voltage-gated calcium channel, which is primarily expressed in the skeletal muscle cells. Pathogenic variants of CACNA1S can cause hypokalemic periodic paralysis (HypoPP), malignant hyperthermia susceptibility, and congenital myopathy. We aimed to study the clinical and molecular features of a male child with a CACNA1S variant and depict the molecular sub-regional characteristics of different phenotypes associated with CACNA1S variants. CASE PRESENTATION: We presented a case of HypoPP with recurrent muscle weakness and hypokalemia. Genetic analyses of the family members revealed that the proband had a novel c.497 C > A (p.Ala166Asp) variant of CACNA1S, which was inherited from his father. The diagnosis of HypoPP was established in the proband as he met the consensus diagnostic criteria. The patient and his parents were informed to avoid the classical triggers of HypoPP. The attacks of the patient are prevented by lifestyle changes and nutritional counseling. We also showed the molecular sub-regional location of the variants of CACNA1S which was associated with different phenotypes. CONCLUSIONS: Our results identified a new variant of CACNA1S and expanded the spectrum of variants associated with HypoPP. Early genetic diagnosis can help avoid diagnostic delays, perform genetic counseling, provide proper treatment, and reduce morbidity and mortality.

Long-term effectiveness and seizure recurrence risk factors of ketogenic diet for pediatric refractory epilepsy: Experience from a tertiary care center in China.

OBJECTIVE: This study aimed to assess the long-term effectiveness and seizure recurrence risk in children with drug-resistant epilepsy who achieved seizure freedom on a ketogenic diet (KD). Predictors associated with seizure recurrence were also evaluated. METHODS: Patients with drug-resistant epilepsy who received KD therapy for at least 3 months between May 2011 and April 2020 were included. The clinical efficacy of the KD was evaluated. Patients who achieved seizure freedom for at least 3 months on the KD were focused. Multivariate Cox regression models were used to explore the risk factors of seizure relapse in patients who achieved seizure freedom. RESULTS: This study included 288 patients (163 males, 125 females). The seizure-free rates of the KD at 3, 6, 12, and 24 months were 9.7%, 16.7%, 14.2%, and 9.0%, respectively. Additionally, the seizure reduction rates between 50% and 99% were 46.5%, 39.9%, 30.2%, and 20.5%, respectively. Patients with Angelman syndrome (AS) showed the highest efficacy rate, followed by those with Dravet syndrome (DS). 51 patients achieved at least 3 months of seizure freedom on the KD. Seizures recurred in 24 (47.1%) patients. None of the patients with AS relapsed, while those with DS had the highest recurrence rate. The etiology of epilepsy, KD maintenance treatment period, and electroencephalography (EEG) abnormalities during follow-up differed significantly between patients with and without recurrence. However, multivariate Cox regression analysis indicated that a KD maintenance treatment period of less than 12 months and the presence of EEG abnormalities during follow-up were significantly correlated with a higher risk of relapse. Epilepsy control was restored in 3 of the 24 (12.5%) patients who experienced relapse. SIGNIFICANCE: KD appears to be effective in children with various types of drug-resistant epilepsy. A short KD maintenance treatment period and EEG abnormalities during follow-up were associated with an increased risk of seizure recurrence.

The application of contrast-enhanced ultrasound for sentinel lymph node evaluation and mapping in breast cancer patients.

Background: To retrospectively investigate the application of contrast-enhanced ultrasound on sentinel lymph node (SLN-CEUS) for SLN evaluation and mapping in breast cancer patients. Methods: Patients diagnosed with breast cancer at the First Affiliated Hospital of Sun Yat-sen University from June 2019 to March 2021 were conveniently evaluated by SLN-CEUS. The results of SLN-CEUS and B mode-ultrasound (BUS) were collected and compared. For patients who only underwent SLN-CEUS, we conducted a 1:1 propensity score matching (PSM). The diagnostic parameters, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), false negative rate (FNR), false positive rate (FPR), and proportion of undetermined diagnoses were compared between the SLN-CEUS and BUS cohorts. The identification rate and FNR of sentinel lymph node biopsy (SLNB) were also assessed. Results: There were 327 patients in each of the SLN-CEUS and BUS cohorts. Among the entire cohort, both NPV [90.2% (95% CI, 85.4-93.5%) vs. 83.5% (95% CI, 77.8-88.0%), P=0.048] and accuracy [80.7% (95% CI, 76.5-85.0%) vs. 73.7% (95% CI, 68.9-78.5%), P<0.001] of SLN-CEUS were significantly higher than those of BUS. In non-neoadjuvant treatment (NAT) patients, the NPV [94.7% (95% CI, 89.9-97.4%) vs. 85.5% (95% CI, 79.1-90.2%), P=0.007] and accuracy [87.6% (95% CI, 83.2-92.0%) vs. 76.0% (95% CI, 70.4-81.5%), P<0.001] of SLN-CEUS were significantly higher than those of BUS. In NAT patients, no difference in diagnostic efficacy was found. The proportion of undetermined diagnoses of SLN-CEUS was significantly lower than that of BUS (5.8% vs. 15.3%, P<0.001). The identification rate of SLN-CEUS in overall patients, non-NAT patients, and NAT patients was 94.2%, 96.3%, and 89.9%, respectively. The FNR of SLNB with the blue-dye tracer in combination with SLN-CEUS in overall patients, non-NAT patients, and NAT patients was 7.3%, 4.0%, and 12.5%, respectively. Conclusions: Compared to BUS, SLN-CEUS is a better technique for diagnosing SLNs in early breast cancer patients, showing superiority in multiple diagnostic parameters. However, the diagnostic value of SLN-CEUS in NAT patients is still undetermined. SLN-CEUS is a promising mapping method in SLNB, with a high identification rate and a low FNR when used in combination with a blue-dye tracer.

The Synergistic Effect of Proanthocyanidin and HDAC Inhibitor Inhibit Breast Cancer Cell Growth and Promote Apoptosis.

Histone deacetylase inhibitor (HDACi) is a drug mainly used to treat hematological tumors and breast cancer, but its inhibitory effect on breast cancer falls short of expectations. Grape seed proanthocyanidin extract (GSPE) with abundant proanthocyanidins (PAs) has been explored for its inhibition of HDAC activity in vitro and in vivo. To enhance HDACi's effectiveness, we investigated the potential of PA to synergistically enhance HDACi chidamide (Chi), and determined the underlying mechanism. We evaluated the half-inhibitory concentration (IC50) of PA and Chi using the cell counting kit 8 (CCK8), and analyzed drugs' synergistic effect with fixed-ratio combination using the software Compusyn. Breast cancer cell's phenotypes, including short-term and long-term proliferation, migration, invasion, apoptosis, and reactive oxygen species (ROS) levels, were assessed via CCK8, clone-formation assay, wound-healing test, Transwell Matrigel invasion assay, and flow-cytometry. Protein-protein interaction analysis (PPI) and KEGG pathway analysis were used to determine the underlying mechanism of synergy. PA + Chi synergistically inhibited cell growth in T47D and MDA-MB-231 breast cancer cell lines. Short-term and long-term proliferation were significantly inhibited, while cell apoptosis was promoted. Ten signaling pathways were identified to account for the synergistic effect after RNA sequencing. Their synergism may be closely related to the steroid biosynthesis and extracellular matrix (ECM) receptor interaction pathways. PA + Chi can synergistically inhibit breast cancer cell growth and proliferation, and promote apoptosis. These effects may be related to steroid biosynthesis or the ECM receptor pathway.

The Efficacy of Low-Kilovoltage X-Rays Intraoperative Radiation as Boost for Breast Cancer: A Systematic Review and Meta-Analysis.

Background: Intraoperative radiotherapy (IORT) is a novel promising technology that may replace external beam radiation therapy (EBRT) as boost for patients receiving breast-conserving surgery. To better evaluate the efficacy of IORT using low-kilovoltage (low-kV) X-rays as boost, we presented this meta-analysis according to the PRISMA checklist. Methods: Studies reported survival outcomes of intraoperative radiation using low-kilovoltage X-rays system (Intrabeam®, Carl Zeiss Meditec, Dublin, CA, USA) as boost were identified through electronic bibliographic database: PUBMED. The meta-analysis module in Stata (16.0) is used to pool the studies. A Poisson regression model is used to predict a 5-year local recurrence rate. Results: Twelve studies including 3006 cases were included in the final analysis, with a median follow-up of 55 months weighted by sample size. The pooled local recurrence rate is 0.39% per person-year (95% CI: 0.15%-0.71%), with a low degree of heterogeneity (I2 = 0%). The predicted 5-year local recurrence rate was 3.45%. No difference in pooled local recurrence rate was found between non-neoadjuvant patients studies and neoadjuvant patients studies (0.41% per person-year vs. 0.58% per person-year, P = 0.580). Conclusions: This study shows that low-kV IORT is an effective method as boost in breast cancer patients, with a low pooled local recurrence rate and low predicted 5-year local recurrence rate. Besides, no difference in the local recurrence rate was found between non-neoadjuvant patients studies and neoadjuvant patients studies. Low-kV IORT boost may be a promising alternative to EBRT boost in the future, which is being tested in the ongoing TARGIT-B trial.

Perspectively Equivariant Keypoint Learning for Omnidirectional Images.

Robust keypoint detection on omnidirectional images against large perspective variations, is a key problem in many computer vision tasks. In this paper, we propose a perspectively equivariant keypoint learning framework named OmniKL for addressing this problem. Specifically, the framework is composed of a perspective module and a spherical module, each one including a keypoint detector specific to the type of the input image and a shared descriptor providing uniform description for omnidirectional and perspective images. In these detectors, we propose a differentiable candidate position sorting operation for localizing keypoints, which directly sorts the scores of the candidate positions in a differentiable manner and returns the globally top-K keypoints on the image. This approach does not break the differentiability of the two modules, thus they are end-to-end trainable. Moreover, we design a novel training strategy combining the self-supervised and co-supervised methods to train the framework without any labeled data. Extensive experiments on synthetic and real-world 360° image datasets demonstrate the effectiveness of OmniKL in detecting perspectively equivariant keypoints on omnidirectional images. Our source code are available online at https://github.com/vandeppce/sphkpt.

A System of Emotion Recognition and Judgment and Its Application in Adaptive Interactive Game.

A system of emotion recognition and judgment (SERJ) based on a set of optimal signal features is established, and an emotion adaptive interactive game (EAIG) is designed. The change in a player's emotion can be detected with the SERJ during the process of playing the game. A total of 10 subjects were selected to test the EAIG and SERJ. The results show that the SERJ and designed EAIG are effective. The game adapted itself by judging the corresponding special events triggered by a player's emotion and, as a result, enhanced the player's game experience. It was found that, in the process of playing the game, a player's perception of the change in emotion was different, and the test experience of a player had an effect on the test results. A SERJ that is based on a set of optimal signal features is better than a SERJ that is based on the conventional machine learning-based method.

TFA-Net: A Deep Learning-Based Time-Frequency Analysis Tool.

Recently, synchrosqueenzing transform (SST)-based time-frequency analysis (TFA) methods have been developed for achieving the highly concentrated TF representation (TFR). However, SST-based methods suffer from two drawbacks. The first one is that the TFRs are unsatisfactory when dealing with the multicomponent signals, the instantaneous frequencies (IFs) of which are closely adjacent or intersected. Besides, the exhaustive adjustment of window length is required for SST-based methods to obtain the optimal TFR. To tackle these problems, in this article, we first analyze the concentration of TFRs for SST-based methods. A deep learning (DL)-based end-to-end replacement scheme for SST-based methods, named TFA-Net, is then proposed, which learns complete basis functions to obtain various TF characteristics of time series. The 2-D filter kernels are subsequently used for energy concentration. Different from the two-step SST-based methods where the TF transform and energy concentration are separated, the proposed end-to-end architecture makes the basis functions used for extracting TF features more beneficial to energy concentration. The comprehensive numerical experiments are conducted to demonstrate the effectiveness of the TFA-Net. The applications of the proposed method to real-world vital signs, undersea voices and micro-Doppler signatures show its great potential in analyzing nonstationary signals.

The application of metagenomic next-generation sequencing for Angiostrongylus eosinophilic meningitis in a pediatric patient: A case report.

Background: Angiostrongylus eosinophilic meningitis (AEM) is a rare yet emerging disease caused by Angiostrongylus cantonensis infection. Its atypical symptoms may delay the diagnosis and cause fatal outcomes, especially in the early stages of infection and among children. Case presentation: Here we reported the use of metagenomic next-generation sequencing (mNGS) to facilitate the diagnosis and treatment of an 8-year-old boy with severe A. cantonensis infection. The mNGS tests consistently identified the infection of A. cantonensis prior to the detection by the immunologic method and confirmed it as AEM. Owing to the multidisciplinary team (MDT)-administrated treatments and close disease monitoring based on regular clinical tests and sequential mNGS tests, the patients eventually fully recovered from severe infectious conditions. Conclusion: This case demonstrated the advantages of mNGS for early diagnosis of AEM in pediatric patients, highlighting its application for pan-pathogen detection, as well as disease monitoring for severe A. cantonensis infection.

Distinct molecular subtypes of papillary thyroid carcinoma and gene signature with diagnostic capability.

Papillary thyroid carcinoma (PTC) is heterogeneous and its molecular characteristics remain elusive. We integrated transcriptomic sequencing, genomic analysis and clinicopathologic information from 582 tissue samples of 216 PTC and 75 benign thyroid nodule (BTN) patients. We discovered four subtypes of PTC including Immune-enriched Subtype, BRAF-enriched Subtype, Stromal Subtype and CNV-enriched Subtype. Molecular subtypes were validated in an external cohort of 497 PTC cases from the TCGA. Tumors in the Immune-enriched Subtype showed higher immune infiltration and overexpression of immune checkpoints, whilst BRAF-enriched Subtype showed a higher tendency for extrathyroidal extension and more advanced TNM stage. Key oncogenes including LRRK2, SLC34A2, MUC1, FOXQ1 and KRT19 were overexpressed and enriched in oncogenic MAPK and PI3K/AKT signaling pathways in BRAF-enriched subtype. Further analysis of BRAF-enriched Subtype identified three subclasses with different degrees of malignancies. We also uncovered the molecular link of the initiation and progression from BTN to subtypes of PTC using trajectory analysis. Moreover, a 20-gene expression signature was generated for differential diagnosis of PTC from BTN patients. Together, our work identified previously unreported molecular subtypes of PTC, offering opportunities to stratify patients into optimal treatment plans based on molecular subtyping.

Interactive Application of Data Glove Based on Emotion Recognition and Judgment System.

In this paper, the interactive application of data gloves based on emotion recognition and judgment system is investigated. A system of emotion recognition and judgment is established based on the set of optimal features of physiological signals, and then a data glove with multi-channel data transmission based on the recognition of hand posture and emotion is constructed. Finally, the system of virtual hand control and a manipulator driven by emotion is built. Five subjects were selected for the test of the above systems. The test results show that the virtual hand and manipulator can be simultaneously controlled by the data glove. In the case that the subjects do not make any hand gesture change, the system can directly control the gesture of the virtual hand by reading the physiological signal of the subject, at which point the gesture control and emotion control can be carried out at the same time. In the test of the manipulator driven by emotion, only the results driven by two emotional trends achieve the desired purpose.

Effects and Mechanisms of Curcumin for the Prevention and Management of Cancers: An Updated Review.

Cancer is the leading cause of death in the world. Curcumin is the main ingredient in turmeric (Curcuma longa L.), and is widely used in the food industry. It shows anticancer properties on different types of cancers, and the underlying mechanisms of action include inhibiting cell proliferation, suppressing invasion and migration, promoting cell apoptosis, inducing autophagy, decreasing cancer stemness, increasing reactive oxygen species production, reducing inflammation, triggering ferroptosis, regulating gut microbiota, and adjuvant therapy. In addition, the anticancer action of curcumin is demonstrated in clinical trials. Moreover, the poor water solubility and low bioavailability of curcumin can be improved by a variety of nanotechnologies, which will promote its clinical effects. Furthermore, although curcumin shows some adverse effects, such as diarrhea and nausea, it is generally safe and tolerable. This paper is an updated review of the prevention and management of cancers by curcumin with a special attention to its mechanisms of action.

Anticancer Effects and Mechanisms of Berberine from Medicinal Herbs: An Update Review.

Cancer has been a serious public health problem. Berberine is a famous natural compound from medicinal herbs and shows many bioactivities, such as antioxidant, anti-inflammatory, antidiabetic, anti-obesity, and antimicrobial activities. In addition, berberine shows anticancer effects on a variety of cancers, such as breast, lung, gastric, liver, colorectal, ovarian, cervical, and prostate cancers. The underlying mechanisms of action include inhibiting cancer cell proliferation, suppressing metastasis, inducing apoptosis, activating autophagy, regulating gut microbiota, and improving the effects of anticancer drugs. This paper summarizes effectiveness and mechanisms of berberine on different cancers and highlights the mechanisms of action. In addition, the nanotechnologies to improve bioavailability of berberine are included. Moreover, the side effects of berberine are also discussed. This paper is helpful for the prevention and treatment of cancers using berberine.

Effects and mechanisms of resveratrol for prevention and management of cancers: An updated review.

Cancer is a severe public health problem. Resveratrol is a famous natural compound that has various bioactivities, such as antioxidant, anti-inflammatory, antidiabetic and antiaging activities. Especially, resveratrol could prevent and treat various cancers, such as oral, thyroid, breast, lung, liver, pancreatic, gastric, colorectal, bladder, prostate and ovarian cancers. The underlying mechanisms have been widely studied, such as inhibiting cell proliferation, suppressing metastasis, inducing apoptosis, stimulating autophagy, modulating immune system, attenuating inflammation, regulating gut microbiota and enhancing effects of other anticancer drugs. In this review, we summarize effects and mechanisms of resveratrol on different cancers. This paper is helpful to develop resveratrol, crude extract containing resveratrol, or foods containing resveratrol into functional food, dietary supplements or auxiliary agents for prevention and management of cancers.

A typical presentation of moxifloxacin-induced DRESS syndrome with pulmonary involvement: a case report and review of the literature.

BACKGROUND: Drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome is a kind of hypersensitivity drug reaction involving the skin and multiple internal organ systems. Moxifloxacin has rarely been reported to be a drug that is associated with DRESS syndrome. Lungs are less frequently involved in DRESS syndrome, but their involvements may herald more serious clinical processes. We present a rare typical case of moxifloxacin-induced DRESS syndrome with lungs involved. Valuable clinical data such as changes in the pulmonary imaging and pulmonary function tests was recorded. This case is important for the differential diagnosis of DRESS syndrome with lungs involved by providing clinical manifestations, CT imaging, pulmonary function tests, and biopsy pathological characteristics. The changes in pulmonary imaging and pulmonary function tests may help us understand the mechanism of DRESS syndrome further. CASE PRESENTATION: We report a case of a 47-year-old woman who was treated with oral moxifloxacin for community-acquired pneumonia. The patient subsequently developed a cough, fever, liver injury, skin rash, hematologic abnormalities, and shortness of breath (SOB) followed by pharyngeal herpes and peripheral neuritis. These symptoms, clinical lab index, and CT scan of the lungs improved after the withdrawal of moxifloxacin. The probability of moxifloxacin-induced DRESS syndrome was rated as "Definite", with 7 scores graded by RegiSCAR. A literature search was also performed with "fluoroquinolones," "moxifloxacin," "ciprofloxacin," "levofloxacin," "delafloxacin," and "DRESS" or "drug-induced hypersensitivity syndrome (DIHS)" as the keywords that were put into PubMed. The overall pulmonary involvement was approximately 9.1% (1/11). It is a rare reported case of DRESS syndrome with pulmonary involvement induced by moxifloxacin. We summarized detailed clinical data, including pulmonary imaging and pulmonary function changes. CONCLUSION: This is a rare reported case of DRESS syndrome with pulmonary involvement induced by moxifloxacin. Prompt recognition and correct diagnosis can promote appropriate treatment and accelerate recovery. This case is important for us as a reference in the differential diagnosis of DRESS syndrome and helps us further understand the mechanism of DRESS syndrome.

pH-Regulated Single and Double Charge Inversions on PEI-Coated Surfaces.

The pH-regulated charge inversions on polyethylenimine (PEI)-coated surfaces are indispensable to their applications in biomaterials and nanomaterials. Various PEI-coated surfaces, where single charge inversion happens, have been extensively investigated, while the surfaces where double charge inversion appears are less reported. Here, using a molecular theory, we systematically study the pH-regulated charge density of PEI-coated surfaces. The results suggest whether single or double charge inversion happens depends on PEI affinity to the surface and the bare surface charge density. The region of double charge inversion is much smaller than that of single charge inversion, revealing the reason why double charge inversion is less observed in experiments. Besides, the charge inversions are significantly influenced by the solution condition. The present work provides a useful guideline to the selection of the coated materials and the parameters of PEI solution in the design of PEI-coated surfaces aiming to promote their applications in multifunctional nanomaterials.

Prognosis assessment model based on low serum calcium in patients with acute pulmonary thromboembolism.

BACKGROUND AND OBJECTIVE: The pulmonary embolism severity index (PESI) and simplified PESI (sPESI) are recommended to recognize patients with acute pulmonary thromboembolism (PTE) with low prognosis risk, which is of great significance for treatment. This study aims to verify the influence of hypocalcaemia on the prognosis of patients with PTE and to establish a new prognosis assessment model. METHODS: This is an observational, multicentre study enrolling patients with PTE from February 2010 to June 2020 across 12 Chinese hospitals. Variables in PESI, serum calcium levels and patient survival status as of 5 July 2020 were collected. The area under the curve of the receiver operating characteristic curve, sensitivity, specificity and Youden index were used to evaluate model performance. RESULTS: In the cohort of 4196 patients with PTE, independent associations existed between hypocalcaemia and mid- and long-term mortalities (p <0.05). By including hypocalcaemia, the new 30-day death risk prediction rule, Peking Union Medical College Hospital rule (PUMCH rule), showed significantly higher specificity (0.622 [0.582, 0.661]; p <0.001) than the PESI (0.514 [0.473, 0.554]) and sPESI (0.484 [0.444, 0.525]) and similar sensitivity (0.963 [0.810, 0.999]; p = 0.161) with PESI (0.889 [0.708, 0.976]) and sPESI (0.963 [0.810, 0.999]) in the internal validation cohort. Well-performing predictive validity was also verified on a constructed external validation cohort. CONCLUSION: Hypocalcaemia is independently associated with mid- and long-term PTE mortalities. The PUMCH rule showed significantly higher specificity than the PESI and sPESI and similar sensitivity, which may be used as a prognostic assessment tool for patients with acute PTE.

Deep Learning-Based 2-D Frequency Estimation of Multiple Sinusoidals.

Frequency estimation of 2-D multicomponent sinusoidal signals is a fundamental issue in the statistical signal processing community that arises in various disciplines. In this article, we extend the DeepFreq model by modifying its network architecture and apply it to 2-D signals. We name the proposed framework 2-D ResFreq. Compared with the original DeepFreq framework, the 2-D convolutional implementation of the matched filtering module facilitates the transformation from time-domain signals to frequency-domain signals and reduces the number of network parameters. The additional upsampling layer and stacked residual blocks are designed to perform superresolution. Moreover, we introduce frequency amplitude information into the optimization function to improve the amplitude accuracy. After training, the signals in the test set are forward-mapped to 2-D accurate and high-resolution frequency representations. Frequency and amplitude estimation are achieved by measuring the locations and strengths of the spectral peaks. We conduct numerical experiments to demonstrate the superior performance of the proposed architecture in terms of its superresolution capability and estimation accuracy.