Carbon and Nitrogen Isotope Fractionations During Biotic and Abiotic Transformations of 2,4-Dinitroanisole (DNAN).

2,4-Dinitroanisole (DNAN) is a main constituent in various new insensitive munition formulations. Although DNAN is susceptible to biotic and abiotic transformations, in many environmental instances, transformation mechanisms are difficult to resolve, distinguish, or apportion on the basis solely of analysis of concentrations. We used compound-specific isotope analysis (CSIA) to investigate the characteristic isotope fractionations of the biotic (by three microbial consortia and three pure cultures) and abiotic (by 9,10-anthrahydroquinone-2-sulfonic acid [AHQS]) transformations of DNAN. The correlations of isotope enrichment factors (ΛN/C) for biotic transformations had a range of values from 4.93 ± 0.53 to 12.19 ± 1.23, which is entirely distinct from ΛN/C values reported previously for alkaline hydrolysis, enzymatic hydrolysis, reduction by Fe2+-bearing minerals and iron-oxide-bound Fe2+, and UV-driven phototransformations. The ΛN/C value associated with the abiotic reduction by AHQS was 38.76 ± 2.23, within the range of previously reported values for DNAN reduction by Fe2+-bearing minerals and iron-oxide-bound Fe2+, albeit the mean ΛN/C was lower. These results enhance the database of isotope effects accompanying DNAN transformations under environmentally relevant conditions, allowing better evaluation of the extents of biotic and abiotic transformations of DNAN that occur in soils, groundwaters, surface waters, and the marine environment.

Machine learning models to evaluate mortality in pediatric patients with pneumonia in the intensive care unit.

OBJECTIVES: This study aimed to predict mortality in children with pneumonia who were admitted to the intensive care unit (ICU) to aid decision-making. STUDY DESIGN: Retrospective cohort study conducted at a single tertiary hospital. PATIENTS: This study included children who were admitted to the pediatric ICU at the National Taiwan University Hospital between 2010 and 2019 due to pneumonia. METHODOLOGY: Two prediction models were developed using tree-structured machine learning algorithms. The primary outcomes were ICU mortality and 24-h ICU mortality. A total of 33 features, including demographics, underlying diseases, vital signs, and laboratory data, were collected from the electronic health records. The machine learning models were constructed using the development data set, and performance matrices were computed using the holdout test data set. RESULTS: A total of 1231 ICU admissions of children with pneumonia were included in the final cohort. The area under the receiver operating characteristic curves (AUROCs) of the ICU mortality model and 24-h ICU mortality models was 0.80 (95% confidence interval [CI], 0.69-0.91) and 0.92 (95% CI, 0.86-0.92), respectively. Based on feature importance, the model developed in this study tended to predict increased mortality for the subsequent 24 h if a reduction in the blood pressure, peripheral capillary oxygen saturation (SpO2), or higher partial pressure of carbon dioxide (PCO2) were observed. CONCLUSIONS: This study demonstrated that the machine learning models for predicting ICU mortality and 24-h ICU mortality in children with pneumonia have the potential to support decision-making, especially in resource-limited settings.

Anti-Hypertensive Effect of Solanum muricatum Aiton Leaf Extract In Vivo and In Vitro.

Hypertension is a global health problem and leads to cardiovascular disease and renal injury. Solanum muricatum Aiton leaf extract, rich in flavonoids, is known for its antioxidant capacity. However, the effects of Solanum muricatum Aiton leaf extract on hypertension combined with inflammatory complications were unknown. This study aimed to investigate the impact of Solanum muricatum Aiton leaf extract on hypertension in vivo and in vitro. In vivo, Solanum muricatum Aiton leaf extract led to decrease high blood pressure, improve heart, aorta, and kidney pathology, and enhance the antioxidative activity in spontaneously hypertensive rats (SHR). Our study demonstrated Solanum muricatum Aiton leaf extract inhibited angiotensin-converting enzyme (ACE), epithelial sodium channel (ENaC), sodium glucose co-transporters-1 (SGLT-1), nuclear factor kappa B (NF-κB), cyclooxygenase-2 (COX-2), inducible nitric oxide synthase (iNOS), tumor necrosis factor-α (TNF-α), interleukin-1ß (IL-1ß), and interleukin-6 (IL-6). In vitro, Solanum muricatum Aiton leaf extract improved the angiotensin II-induced reactive oxygen species (ROS) and mitochondrial membrane depolarization in NRK-52E cells. Besides, Solanum muricatum Aiton leaf extract could also decrease the expressions of ENaC, SGLT-1, and NF-κB in angiotensin II-treated NRK-52E cells. Solanum muricatum Aiton leaf can be suggested as a novel antihypertensive agent ameliorating hypertension via ACE inhibition, inflammation reduction, and ROS. PLE is a novel anti-hypertensive agent to ameliorate hypertension and its complications, including inflammation.

Pyrogenic Black Carbon Suppresses Microbial Methane Production by Serving as a Terminal Electron Acceptor.

Methane (CH4) is the second most important greenhouse gas, 27 times as potent as CO2 and responsible for >30% of the current anthropogenic warming. Globally, more than half of CH4 is produced microbially through methanogenesis. Pyrogenic black carbon possesses a considerable electron storage capacity (ESC) and can be an electron donor or acceptor for abiotic and microbial redox transformation. Using wood-derived biochar as a model black carbon, we demonstrated that air-oxidized black carbon served as an electron acceptor to support anaerobic oxidation of organic substrates, thereby suppressing CH4 production. Black carbon-respiring bacteria were immediately active and outcompeted methanogens. Significant CH4 did not form until the bioavailable electron-accepting capacity of the biochar was exhausted. An experiment with labeled acetate (13CH3COO-) yielded 1:1 13CH4 and 12CO2 without biochar and predominantly 13CO2 with biochar, indicating that biochar enabled anaerobic acetate oxidation at the expense of methanogenesis. Methanogens were enriched following acetate fermentation but only in the absence of biochar. The electron balance shows that approximately half (∼2.4 mmol/g) of biochar's ESC was utilized by the culture, corresponding to the portion of the ESC > +0.173 V (vs SHE). These results provide a mechanistic basis for quantifying the climate impact of black carbon and developing ESC-based applications to reduce CH4 emissions from biogenic sources.

Linear Free Energy Relationship for Predicting the Rate Constants of Munition Compound Reduction by the Fe(II)-Hematite and Fe(II)-Goethite Redox Couples.

Abiotic reduction by iron minerals is arguably the most important fate process for munition compounds (MCs) in subsurface environments. No model currently exists that can predict the abiotic reduction rates of structurally diverse MCs by iron (oxyhydr)oxides. We performed batch experiments to measure the rate constants for the reduction of three classes of MCs (poly-nitroaromatics, nitramines, and azoles) by hematite or goethite in the presence of aqueous Fe2+. The surface area-normalized reduction rate constant (kSA) depended on the aqueous-phase one-electron reduction potential (EH1) of the MC and the thermodynamic state (i.e., pe and pH) of the iron oxide-Feaq2+ system. A linear free energy relationship (LFER), similar to that reported previously for nitrobenzene, successfully captures all MC reduction rate constants that span 6 orders of magnitude: log(kSA)=(1.12±0.04)[0.53EH159mV-(pH+pe)]+(5.52±0.23). The finding that the rate constants of all the different classes of MCs can be described by a single LFER suggests that these structurally diverse nitro compounds are reduced by iron oxide-Feaq2+ couples through a common mechanism up to the rate-limiting step. Multiple mechanistic implications of the results are discussed. This study expands the applicability of the LFER model for predicting the reduction rates of legacy and emerging MCs and potentially other nitro compounds.

Thermodynamic Two-Site Surface Reaction Model for Predicting Munition Constituent Reduction Kinetics with Iron (Oxyhydr)oxides.

Iron (oxyhydr)oxides comprise a significant portion of the redox-active fraction of soils and are key reductants for remediation of sites contaminated with munition constituents (MCs). Previous studies of MC reduction kinetics with iron oxides have focused on the concentration of sorbed Fe(II) as a key parameter. To build a reaction kinetic model, it is necessary to predict the concentration of sorbed Fe(II) as a function of system conditions and the redox state. A thermodynamic framework is formulated that includes a generalized double-layer model that utilizes surface acidity and surface complexation reactions to predict sorbed Fe(II) concentrations that are used for fitting MC reduction kinetics. Monodentate- and bidentate Fe(II)-binding sites are used with individual oxide sorption characteristics determined through data fitting. Results with four oxides (goethite, hematite, lepidocrocite, and ferrihydrite) and four nitro compounds (NB, CN-NB, Cl-NB, and NTO) from six separate studies have shown good agreement when comparing observed and predicted surface area-normalized rate constants. While both site types are required to reproduce the experimental redox titration, only the monodentate site concentration controls the MC reaction kinetics. This model represents a significant step toward predicting the timescales of MC degradation in the subsurface.

Design, Synthesis, and Evaluation of Glucose Transporter Inhibitor-SN38 Conjugates for Targeting Colorectal Cancer.

Irinotecan (1), a prodrug of SN38 (2) approved by the US Food and Drug Administration for treating colorectal cancer, lacks specificity and causes many side effects. To increase the selectivity and therapeutic efficacy of this drug, we designed and synthesized conjugates of SN38 and glucose transporter inhibitors (phlorizin (5) or phloretin (6)), which could be hydrolyzed by glutathione or cathepsin to release SN38 in the tumor microenvironment, as a proof of concept. These conjugates (8, 9, and 10) displayed better antitumor efficacy with lower systemic exposure to SN38 in an orthotopic colorectal cancer mouse model compared with irinotecan at the same dosage. Further, no major adverse effects of the conjugates were observed during treatment. Biodistribution studies showed that conjugate 10 could induce higher concentrations of free SN38 in tumor tissues than irinotecan at the same dosage. Thus, the developed conjugates exhibit potential for treating colorectal cancer.

Isolation of Anti-SARS-CoV-2 Natural Products Extracted from Mentha canadensis and the Semi-synthesis of Antiviral Derivatives.

Traditional herbal medicine offers opportunities to discover novel therapeutics against SARS-CoV-2 mutation. The dried aerial part of mint (Mentha canadensis L.) was chosen for bioactivity-guided extraction. Seven constituents were isolated and characterized by nuclear magnetic resonance (NMR) and mass spectrometry (MS). Syringic acid and methyl rosmarinate were evaluated in drug combination treatment. Ten amide derivatives of methyl rosmarinate were synthesized, and the dodecyl (13) and 3-ethylphenyl (19) derivatives demonstrated significant improvement in the anti-SARS-CoV-2 plaque reduction assay, achieving IC50 of 0.77 and 2.70 µM, respectively, against Omicron BA.1 as compared to methyl rosmarinate's IC50 of 57.0 µM. Spike protein binding and 3CLpro inhibition assays were performed to explore the viral inhibition mechanism. Molecular docking of compounds 13 and 19 to 3CLpro was performed to reveal potential interaction. In summary, natural products with anti-Omicron BA.1 activity were isolated from Mentha canadensis and derivatives of methyl rosmarinate were synthesized, showing 21- to 74-fold improvement in antiviral activity against Omicron BA.1.

Combating breast cancer progression through combination therapy with hypomethylating agent and glucocorticoid.

Breast cancer is the leading cause of cancer-related death in women. Among breast cancer types, triple-negative breast cancer (TNBC) accounts for 15% of all breast cancers with aggressive tumor behavior. By using bioinformatic approaches, we observed that the microRNA-708 promoter is highly methylated in breast carcinomas, and this methylation is linked to a poor prognosis. Moreover, microRNA-708 expression correlates with better clinical outcomes in TNBC patients. Combination treatment with the hypomethylating agent decitabine and synthetic glucocorticoid significantly increased the expression of microRNA-708, reactivated DNMT-suppressed pathways, and decreased the expression of multiple metastasis-promoting genes such as matrix metalloproteinases (MMPs) and IL-1ß, leading to the suppression of breast cancer cell proliferation, migration, and invasion, as well as reduced tumor growth and distant metastasis in the TNBC xenograft mouse model. Overall, our study reveals a therapeutic opportunity in which a combined regimen of decitabine with glucocorticoid may have therapeutic potential in treating TNBC patients.

Clinical characteristics of hospitalized children with community-acquired pneumonia and respiratory infections: Using machine learning approaches to support pathogen prediction at admission.

BACKGROUND: Acute respiratory infections (ARIs) are common in children. We developed machine learning models to predict pediatric ARI pathogens at admission. METHODS: We included hospitalized children with respiratory infections between 2010 and 2018. Clinical features were collected within 24 h of admission to construct models. The outcome of interest was the prediction of 6 common respiratory pathogens, including adenovirus, influenza virus types A and B, parainfluenza virus (PIV), respiratory syncytial virus (RSV), and Mycoplasma pneumoniae (MP). Model performance was estimated using area under the receiver operating characteristic curve (AUROC). Feature importance was measured using Shapley Additive exPlanation (SHAP) values. RESULTS: A total of 12,694 admissions were included. Models trained with 9 features (age, event pattern, fever, C-reactive protein, white blood cell count, platelet count, lymphocyte ratio, peak temperature, peak heart rate) achieved the best performance (AUROC: MP 0.87, 95% CI 0.83-0.90; RSV 0.84, 95% CI 0.82-0.86; adenovirus 0.81, 95% CI 0.77-0.84; influenza A 0.77, 95% CI 0.73-0.80; influenza B 0.70, 95% CI 0.65-0.75; PIV 0.73, 95% CI 0.69-0.77). Age was the most important feature to predict MP, RSV and PIV infections. Event patterns were useful for influenza virus prediction, and C-reactive protein had the highest SHAP value for adenovirus infections. CONCLUSION: We demonstrate how artificial intelligence can assist clinicians identify potential pathogens associated with pediatric ARIs upon admission. Our models provide explainable results that could help optimize the use of diagnostic testing. Integrating our models into clinical workflows may lead to improved patient outcomes and reduce unnecessary medical costs.

Design, structure-activity relationships, and enzyme kinetic studies of tricyclic and tetracyclic coumarin-based sulfamates as steroid sulfatase inhibitors.

Inhibition of steroid sulfatase (STS) decreases estrogen production and thus, suppresses tumor proliferation. Inspired by irosustat, the first STS inhibitor in clinical trials, we explored twenty-one tricyclic and tetra-heterocyclic coumarin-based derivatives. Their STS enzyme kinetic parameters, docking models, and cytotoxicity toward breast cancer and normal cells were evaluated. Tricyclic derivative 9e and tetracyclic derivative 10c were the most promising irreversible inhibitors developed in this study, with KI of 0.05 and 0.4 nM, and kinact/KI ratios of 28.6 and 19.1 nM-1min-1 on human placenta STS, respectively.

Longitudinal changes in swallowing function after surgery and proactive swallowing therapy for oral cancer.

BACKGROUND: This study aimed to describe and explore the longitudinal changes in swallowing function among patients with oral cancer who underwent surgery and proactive swallowing therapy from baseline to 1-year postoperation. METHODS: We retrospectively studied 118 patients over a 4.5-year duration. Swallowing functional assessment including 10-item Eating Assessment Tool (EAT-10), Functional Oral Intake Scale (FOIS), M. D. Anderson Dysphagia Inventory, and Modified Barium Swallow Impairment Profile (MBSImP™) was performed at baseline, 1-month, 6-month, and 1-year postoperatively. RESULTS: All swallowing parameters worsened 1-month postoperation. EAT-10, FOIS, and MBSImP™ oral and pharyngeal impairment scores improved significantly compared with 1-month postoperation at 6 months. Other swallowing parameters, except for weight, did not differ significantly from baseline at 6 months. The rate of tube-feeding dependency was 11.5% and 5.6% at 1 and 6 months postoperation, respectively. CONCLUSIONS: Periodic swallowing functional assessments help delineate the longitudinal changes in swallowing functional outcomes.

A myeloid leukemia factor homolog is involved in tolerance to stresses and stress-induced protein metabolism in Giardia lamblia.

BACKGROUND: The eukaryotic membrane vesicles contain specific sets of proteins that determine vesicle function and shuttle with specific destination. Giardia lamblia contains unknown cytosolic vesicles that are related to the identification of a homolog of human myeloid leukemia factor (MLF) named MLF vesicles (MLFVs). Previous studies suggest that MLF also colocalized with two autophagy machineries, FYVE and ATG8-like protein, and that MLFVs are stress-induced compartments for substrates of the proteasome or autophagy in response to rapamycin, MG132, and chloroquine treatment. A mutant protein of cyclin-dependent kinase 2, CDK2m3, was used to understand whether the aberrant proteins are targeted to degradative compratments. Interestingly, MLF was upregulated by CDK2m3 and they both colocalized within the same vesicles. Autophagy is a self-digestion process that is activated to remove damaged proteins for preventing cell death in response to various stresses. Because of the absence of some autophagy machineries, the mechanism of autophagy is unclear in G. lamblia. RESULTS: In this study, we tested the six autophagosome and stress inducers in mammalian cells, including MG132, rapamycin, chloroquine, nocodazole, DTT, and G418, and found that their treatment increased reactive oxygen species production and vesicle number and level of MLF, FYVE, and ATG8-like protein in G. lamblia. Five stress inducers also increased the CDK2m3 protein levels and vesicles. Using stress inducers and knockdown system for MLF, we identified that stress induction of CDK2m3 was positively regulated by MLF. An autophagosome-reducing agent, 3-methyl adenine, can reduce MLF and CDK2m3 vesicles and proteins. In addition, knockdown of MLF with CRISPR/Cas9 system reduced cell survival upon treatment with stress inducers. Our newly developed complementation system for CRISPR/Cas9 indicated that complementation of MLF restored cell survival in response to stress inducers. Furthermore, human MLF2, like Giardia MLF, can increase cyst wall protein expression and cyst formation in G. lamblia, and it can colocalize with MLFVs and interact with MLF. CONCLUSIONS: Our results suggest that MLF family proteins are functionally conserved in evolution. Our results also suggest an important role of MLF in survival in stress conditions and that MLFVs share similar stress-induced characteristics with autophagy compartments.

MicroRNA-708 emerges as a potential candidate to target undruggable NRAS.

RAS, the most frequently mutated oncogene that drives tumorigenesis by promoting cell proliferation, survival, and motility, has been perceived as undruggable for the past three decades. However, intense research in the past has mainly focused on KRAS mutations, and targeted therapy for NRAS mutations remains an unmet medical need. NRAS mutation is frequently observed in several cancer types, including melanoma (15-20%), leukemia (10%), and occasionally other cancer types. Here, we report using miRNA-708, which targets the distinct 3' untranslated region (3'UTR) of NRAS, to develop miRNA-based precision medicine to treat NRAS mutation-driven cancers. We first confirmed that NRAS is a direct target of miRNA-708. Overexpression of miRNA-708 successfully reduced NRAS protein levels in melanoma, leukemia, and lung cancer cell lines with NRAS mutations, resulting in suppressed cell proliferation, anchorage-independent growth, and promotion of reactive oxygen species-induced apoptosis. Consistent with the functional data, the activities of NRAS-downstream effectors, the PI3K-AKT-mTOR or RAF-MEK-ERK signaling pathway, were impaired in miR-708 overexpressing cells. On the other hand, cell proliferation was not disturbed by miRNA-708 in cell lines carrying wild-type NRAS. Collectively, our data unveil the therapeutic potential of using miRNA-708 in NRAS mutation-driven cancers through direct depletion of constitutively active NRAS and thus inhibition of its downstream effectors to decelerate cancer progression. Harnessing the beneficial effects of miR-708 may therefore offer a potential avenue for small RNA-mediated precision medicine in cancer treatment.

Unraveling the molecular mechanism of collagen flexibility during physiological warmup using molecular dynamics simulation and machine learning.

Physiological warmup plays an important role in reducing the injury risk in different sports. In response to the associated temperature increase, the muscle and tendon soften and become easily stretched. In this study, we focused on type I collagen, the main component of the Achilles tendon, to unveil the molecular mechanism of collagen flexibility upon slight heating and to develop a model to predict the strain of collagen sequences. We used molecular dynamics approaches to simulate the molecular structures and mechanical behavior of the gap and overlap regions in type I collagen at 307 K, 310 K, and 313 K. The results showed that the molecular model in the overlap region is more sensitive to temperature increases. Upon increasing the temperature by 3 degrees Celsius, the end-to-end distance and Young's modulus of the overlap region decreased by 5% and 29.4%, respectively. The overlap region became more flexible than the gap region at higher temperatures. GAP-GPA and GNK-GSK triplets are critical for providing molecular flexibility upon heating. A machine learning model developed from the molecular dynamics simulation results showed good performance in predicting the strain of collagen sequences at a physiological warmup temperature. The strain-predictive model could be applied to future collagen designs to obtain desirable temperature-dependent mechanical properties.

Electron Transfer Energy and Hydrogen Atom Transfer Energy-Based Linear Free Energy Relationships for Predicting the Rate Constants of Munition Constituent Reduction by Hydroquinones.

No single linear free energy relationship (LFER) exists that can predict reduction rate constants of all munition constituents (MCs). To address this knowledge gap, we measured the reduction rates of MCs and their surrogates including nitroaromatics [NACs; 2,4,6-trinitrotoluene (TNT), 2,4-dinitroanisole (DNAN), 2-amino-4,6-dinitrotoluene (2-A-DNT), 4-amino-2,6-dinitrotoluene (4-A-DNT), and 2,4-dinitrotoluene (DNT)], nitramines [hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) and nitroguanidine (NQ)], and azoles [3-nitro-1,2,4-triazol-5-one (NTO) and 3,4-dinitropyrazole (DNP)] by three dithionite-reduced quinones (lawsone, AQDS, and AQS). All MCs/NACs were reduced by the hydroquinones except NQ. Hydroquinone and MC speciations were varied by controlling pH, permitting the application of a speciation model to determine second-order rate constants (k) from observed pseudo-first-order rate constants. The intrinsic reactivity of MCs (oxidants) decreased upon deprotonation, while the opposite was true for hydroquinones (reductants). The rate constants spanned ∼6 orders of magnitude in the order NTO ≈ TNT > DNP > DNT ≈ DNAN ≈ 2-A-DNT > DNP- > 4-A-DNT > NTO- > RDX. LFERs developed using density functional theory-calculated electron transfer and hydrogen atom transfer energies and reported one-electron reduction potentials successfully predicted k, suggesting that these structurally diverse MCs/NACs are all reduced by hydroquinones through the same mechanism and rate-limiting step. These results increase the applicability of LFER models for predicting the fate and half-lives of MCs and related nitro compounds in reducing environments.

Psychological Distress and Physical Adverse Events of COVID-19 Vaccination among Healthcare Workers in Taiwan.

The COVID-19 pandemic places high pressure on everyone, including healthcare workers (HCWs), thus causing them to experience psychological distress. HCWs have priority in receiving the COVID-19 vaccine. However, few studies have identified adverse events (AEs) and psychological distress in the HCWs group. Therefore, we investigated the association between psychological distress and AEs and the determinants of protective behaviors in Taiwanese HCWs. A longitudinal measurement was conducted among HCWs at National Cheng Kung University Hospital (NCKUH), Tainan, Taiwan (n = 483, mean age = 37.55 years). All HCWs completed an online questionnaire on psychological distress, COVID-19 vaccination AEs, and protective behaviors. We used generalized estimating equations (GEE) to analyze the correlation between psychological distress and AEs, and used multivariable logistic regressions to explore the predictors of protective behaviors. Depression and distress and anger were significantly associated with various physical AEs (p = 0.045 to p < 0.001). Suicidal thoughts became a significant independent variable of systemic AEs after COVID-19 vaccination (p = 0.014 to p < 0.001). People of older ages or females engaged more in washing their hands, wearing masks, and reducing their presence in crowded places. Suicidal thoughts were related to the occurrence of systemic AEs among HCWs. Doctors performed better at preventive behaviors compared to nurses and other HCWs. HCWs who experienced anxiety and nervousness tended to avoid crowds.

Deep Learning for Detecting Supraspinatus Calcific Tendinopathy on Ultrasound Images.

Background: The aim of the study was to evaluate the feasibility of convolutional neural network (CNN)-based deep learning (DL) algorithms to dichotomize shoulder ultrasound (US) images with or without supraspinatus calcific tendinopathy (SSCT). Methods: This was a retrospective study pertaining to US examinations that had been performed by 18 physiatrists with 3-20 years of experience. 133,619 US images from 7836 consecutive patients who had undergone shoulder US examinations between January 2017 and June 2019 were collected. Only images with longitudinal or transverse views of supraspinatus tendons (SSTs) were included. During the labeling process, two physiatrists with 6-and 10-year experience in musculoskeletal US independently classified the images as with or without SSCT. DenseNet-121, a pre-trained model in CNN, was used to develop a computer-aided system to identify US images of SSTs with and without calcifications. Testing accuracy, sensitivity, and specificity calculated from the confusion matrix was used to evaluate the models. Results: A total of 2462 images were used for developing the DL algorithm. The longitudinal-transverse model developed with a CNN-based DL algorithm was better for the diagnosis of SSCT when compared with the longitudinal and transverse models (accuracy: 91.32%, sensitivity: 87.89%, and specificity: 94.74%). Conclusion: The developed DL model as a computer-aided system can assist physicians in diagnosing SSCT during the US examination.

The Sprint-Interval Exercise Using a Spinning Bike Improves Physical Fitness and Ameliorates Primary Dysmenorrhea Symptoms Through Hormone and Inflammation Modulations: A Randomized Controlled Trial.

Dysmenorrhea with high prevalence has been categorized as primary dysmenorrhea (PD) and secondary dysmenorrhea due to differences in pathogenesis. A significant number of reproductive females suffering from monthly menstruation have to deal with negative impacts on their quality of life, work/study productivity, activities, and social relationships. In addition to medical treatment, exercise has been recognized as a complementary and alternative strategy for disease prevention, alleviation, and rehabilitation. This study aimed to investigate the potential effects of exercise on the severity of primary dysmenorrhea, physiological modulation, and physical fitness. Participants consisted of university students who were enrolled in the study and divided into a non-PD (Control) and a PD group based on recruiting criteria, the latter being randomly assigned to either an untreated dysmenorrhea group or a dysmenorrhea group that underwent 10 weeks of high intensity interval training (HIIT) exercise (Dysmen and DysmenHIIT, respectively). The DysmenHIIT group used spinning bikes and the training intensity was validated by heart rate monitors and BORG rating of perceived exertion. Forms containing participant information (premenstrual symptoms, menstrual distress, and a Short Form McGill Pain Questionnaire) as well as physical fitness, biochemical variables, hormone and prostaglandin (PGE2 and PGF2α) levels were assessed before and after the exercise intervention. After intervention, premenstrual symptoms (anger, anxiety, depression, activity level, fatigue, etc.), menstrual distress symptoms (cramps, aches, swelling, etc.), and pain severity were shown to be significantly mitigated, possibly through hormone (estradiol, prolactin, progesterone, and cortisol) modulation. Furthermore, high-sensitivity C-reactive protein (HsCRP), PGE2 and PGF2α levels were also down-regulated, resulting in the amelioration of uterine contraction and inflammation. Participants' physical fitness, including cardiovascular endurance and explosive force, was significantly improved after HIIT. The 10-week HIIT spinning bike exercise used in this study could be employed as a potential and complementary treatment for PD symptoms alleviation and considered as part of an educational health plan for promoting women's health. However, the effects of HIIT utilizing different exercise methods and accounting for different age populations and secondary PD warrant further investigation.

The Design, Structure-Activity, and kinetic studies of 3-Benzyl-5-oxa-1,2,3,4-Tetrahydro-2H-chromeno-(3,4-c)pyridin-8-yl sulfamates as Steroid sulfatase inhibitors.

Steroid sulfatase inhibitors block the local production of estrogenic steroids and are attractive agents for the treatment of estrogen-dependent cancers. Inspiration of coumarin-based inhibitors, we synthesized thirty-two 5-oxa-1,2,3,4-tetrahydro-2H-chromeno-(3,4-c)pyridin-8-yl sulfamates, focusing on the substitution derivatives on the adjacent phenyl ring and evaluated their abilities to block STS from human placenta and MCF-7 cells. SAR analysis revealed that the incorporation of chlorine at either meta and/or para position of the adjacent phenyl ring of the tricyclic skeleton enhanced STS inhibition. Di-substitutions at the adjacent phenyl ring were superior to mono and tri-substitutions. Further kinetic analysis of these compounds revealed that chloride-bearing compounds, such as 19m, 19v, and 19w, had KI of 0.02 to 0.11 nM and kinact/KI ratios of 8.8-17.5 nM-1min-1, a parameter indicated for the efficiency of irreversible inhibition. We also used the docking model to illustrate the difference in STS inhibitory potency of compounds. Finally, the safety and anti-cancer activity of selected compounds 19m, 19v, and 19w were also studied, showing the results of low cytotoxicity on NHDF cell line and being more potent than irosustat on ZR-75-1 cell, which was a hormone-dependent cancer cell line with high STS expression.