Sex differences in anhedonia in bipolar depression: a resting-state fMRI study

Previous studies about anhedonia symptoms in bipolar depression (BD) ignored the unique role of gender on brain function. This study aims to explore the regional brain neuroimaging features of BD with anhedonia and the sex differences in these patients. The resting-fMRI by applying fractional amplitude of low-frequency fluctuation (fALFF) method was estimated in 263 patients with BD (174 high anhedonia [HA], 89 low anhedonia [LA]) and 213 healthy controls. The effects of two different factors in patients with BD were analyzed using a 3 (group: HA, LA, HC) × 2 (sex: male, female) ANOVA. The fALFF values were higher in the HA group than in the LA group in the right medial cingulate gyrus and supplementary motor area. For the sex-by-group interaction, the fALFF values of the right hippocampus, left medial occipital gyrus, right insula, and bilateral medial cingulate gyrus were significantly higher in HA males than in LA males but not females. These results suggested that the pattern of high activation could be a marker of anhedonia symptoms in BD males, and the sex differences should be considered in future studies of BD with anhedonia symptoms.

ParTRE: A relational triple extraction model of complicated entities and imbalanced relations in Parkinson's disease

The relational triple extraction of unstructured medical texts about Parkinson's disease is critical for the construction of a medical knowledge graph. However, the triple entities in Parkinson's disease are usually complicated and overlapped, which impedes the accuracy of triple extraction, especially in the case of rarely available corpus. Therefore, this study first builds a corpus about Parkinson's disease. Then, a tagging-based three-stage relational triple extraction model is proposed, named ParTRE. To enhance the contextual representation of sentences, the proposed model employs BiLSTM modules to capture fine-grained semantic information. Additionally, a conditional normalization layer is used so that entity pairs can be extracted accurately from two complementary directions. As for the imbalanced relationship categories, an adaptive loss function strategy based on focal loss is derived by assigning different weights to relationship categories and reducing the loss of easy-to-classify samples. The model performance is evaluated on the Parkinson's corpus and public datasets. The results indicate that the proposed model achieves an overall F1-score of 93.3 % on the Parkinson's corpus and comparable performance on public datasets compared with the state-of-the-art methods. Moreover, a satisfactory result is achieved by the proposed model on conquering the overlapped entities and imbalanced relationship categories. Owing to demonstrated availability and validity, the proposed method can be integrated with medical knowledge graphs and therefore benefits medical intelligence.

Distinct MRI-based functional and structural connectivity for antidepressant response prediction in major depressive disorder

OBJECTIVE

Emerging studies have identified treatment-related connectome predictors in major depressive disorder (MDD). However, quantifying treatment-responsive patterns in structural connectivity (SC) and functional connectivity (FC) simultaneously remains underexplored. We aimed to evaluate whether spatial distributions of FC and SC associated treatment responses are shared or unique.

METHODS

Diffusion tensor imaging and resting-state functional magnetic resonance imaging were collected from 210 patients with MDD at baseline. We separately developed connectome-based prediction models (CPM) to predict reduction of depressive severity after 6-week monotherapy based on structural, functional, and combined connectomes, then validated them on the external dataset. We identified the predictive SC and FC from CPM with high occurrence frequencies during the cross-validation.

RESULTS

Structural connectomes (r = 0.2857, p < 0.0001), functional connectomes (r = 0.2057, p = 0.0025), and their combined CPM (r = 0.4, p < 0.0001) can significantly predict a reduction of depressive severity. We didn't find shared connectivity between predictive FC and SC. Specifically, the most predictive FC stemmed from the default mode network, while predictive SC was mainly characterized by within-network SC of fronto-limbic networks.

CONCLUSIONS

These distinct patterns suggest that SC and FC capture unique connectivity concerning the antidepressant response.

SIGNIFICANCE

Our findings provide comprehensive insights into the neurophysiology of antidepressants response.

Based on white matter microstructure to early identify bipolar disorder from patients with depressive episode

OBJECTIVE

Because of similar clinical manifestations, bipolar disorder (BD) patients are often misdiagnosed as major depressive disorder (MDD). This study aimed to compare the difference between depressed patients later converting to BD and unipolar depression (UD) according to diffusion tensor imaging (DTI).

METHOD

Patients with MDD (562 participants) in depressive episode states and healthy controls (HCs) (145 participants) were recruited over 10 years. Demographic and magnetic resonance imaging (MRI) data were collected at the time of recruitment. All patients with MDD were followed up for 5 years and classified into the transfer to BD (tBD) group (83 participants) and UD group (160 participants) according to the follow-up results. DTI and functional magnetic resonance imaging at baseline were compared.

RESULTS

Common abnormalities were found in both tBD and UD groups, including left superior cerebellar peduncle (SCP.L), right anterior limb of the internal capsule (ALIC.R), right superior fronto-occipital fasciculus (SFOF.R), and right inferior fronto-occipital fasciculus (IFOF.R). The tBD showed more extensive abnormalities than the UD in the body of corpus callosum, fornix, left superior corona radiata, left posterior corona radiata, left superior longitudinal fasciculus, and left superior fronto-occipital fasciculus.

CONCLUSION

The study demonstrated the common and distinct abnormalities of tBD and UD when compared to HC. The tBD group showed more extensive disruptions of white matter integrity, which could be a potential biomarker for the early identification of BD.

Synthesis of Superelastic, Highly Conductive Graphene Aerogel/Liquid Metal Foam and its Piezoresistive Application

Graphene aerogel (GA) has important application potential as piezoresistive sensors due to its low density, high conductivity, high porosity, and good mechanical properties. However, the fabrication of GA-based sensors with good mechanical properties and excellent sensing performance is still challenging. Herein, liquid- metal-modified GAs (GA/LM) are proposed for the development of an excellent GA-based sensor. GA/LM with three-dimensional interconnected layered structure exhibits excellent compressive stress of 41 KPa and fast response time (<20 ms). While generally flexible GA composites cannot be compressed beyond 80 % strain without plastic deformation, GA/LM demonstrates a high compressive strength of 60 kPa under a strain of 90 %. A real-time pressure sensor was fabricated based on GA/LM-2 to monitor swallowing, pulse beating, finger, wrist and knee bending, and even plantar pressure during walking. These excellent features enable potential applications in health detection.

Intensity and drivers of subtypes interference between seasonal influenza viruses in mainland China: A modeling study

Subtype interference has a significant impact on the epidemiological patterns of seasonal influenza viruses (SIVs). We used attributable risk percent [the absolute value of the ratio of the effective reproduction number (Rₑ) of different subtypes minus one] to quantify interference intensity between A/H1N1 and A/H3N2, as well as B/Victoria and B/Yamagata. The interference intensity between A/H1N1 and A/H3N2 was higher in southern China 0.26 (IQR: 0.11-0.46) than in northern China 0.17 (IQR: 0.07-0.24). Similarly, interference intensity between B/Victoria and B/Yamagata was also higher in southern China 0.14 (IQR: 0.07-0.24) than in norther China 0.10 (IQR: 0.04-0.18). High relative humidity significantly increased subtype interference, with the highest relative risk reaching 20.59 (95% CI: 6.12-69.33) in southern China. Southern China exhibited higher levels of subtype interference, particularly between A/H1N1 and A/H3N2. Higher relative humidity has a more pronounced promoting effect on subtype interference.

Enhancing Surgical Nursing Student Performance: Comparative Study of Simulation-Based Learning and Problem-Based Learning

Background

Surgical nursing is a high-risk, high-pressure, and complex field. Nurses need extensive knowledge, skills, and abilities. Problem-Based Learning (PBL) and Simulation-Based Learning (SBL) are effective student-centered methods. Which method is better for surgical nurse training? More research is needed to determine the best approach for undergraduate surgical nurse education.

Purpose

To compare the impact of PBL and SBL on undergraduate nursing students' performance and improve learning outcomes in surgical nursing education.

Methods

We used a pretest/post-test design with 318 nursing undergraduates randomly assigned to two groups. Participants completed three progressive scenarios focused on surgical nursing cases. Experts blindly reviewed video recordings using the 70-item Korean Nurses' Core Competence Scale (KNCCS) to assess performance. The 13-item Satisfaction and Self-confidence in learning Scale (SSS) measured learning confidence and satisfaction. SBL participants also completed the 16-item Educational Practices in Simulation Scale (EPSS) and 20-item Simulation Design Scale (SDS).

Results

The study found significant positive effects on both groups, with noticeable improvements in post-test, retention, and follow-up test results (P < 0.001). The SBL group showed higher competency levels in nurses (P < 0.001). The Cohen's d and effect size (r) for various skills were as follows: clinical performance (0.84767 and 6.39023), critical thinking (0.31017 and 0.15325), professional attitude (0.85868 and 0.39452), and communication skills (1.55149 and 0.61294). The satisfaction and self-confidence of nurses were higher in the SBL group (4.53±0.596; 4.47±0.611) compared to the PBL group (4.32±0.689; 4.25±0.632) in all dimensions of SSS (all P < 0.05). The SBL group also scored high in simulation design and EPSS. However, improvements are needed in fidelity, objectives, information, and students' expectations.

Conclusion

SBL and PBL improve nurses' core competence, satisfaction, and self-confidence. SBL is superior. This study promotes student-centered education, enhancing surgical nursing professionals' quality and ensuring future patient safety.

2D Nano-Channeled Molybdenum Compounds for Accelerating Interfacial Polysulfides Catalysis in Li-S Battery

The shuttle effect, which causes the loss of active sulfur, passivation of lithium anode, and leads to severe capacity attenuation, is currently the main bottleneck for lithium-sulfur batteries. Recent studies have disclosed that molybdenum compounds possess exceptional advantages as a polar substrate to immobilize and catalyze lithium polysulfide such as high conductivity and strong sulfiphilicity. However, these materials show incomplete contact with sulfur/polysulfides, which causes uneven redox conversion of sulfur and results in poor rate performance. Herein, a new type of 2D nano-channeled molybdenum compounds (2D-MoNx) via the 2D organic-polyoxometalate superstructure for accelerating interfacial polysulfide catalysis toward high-performance lithium-sulfur batteries is reported. The 2D-MoNx shows well-interlinked nano-channels, which increase the reactive interface and contact surface with polysulfides. Therefore, the battery equipped with 2D-MoNx displays a high discharge capacity of 912.7 mAh g-1 at 1 C and the highest capacity retention of 523.7 mAh g-1 after 300 cycles. Even at the rate of 2 C, the capacity retention can be maintained at 526.6 mAh g-1 after 300 cycles. This innovative nano-channel and interfacial design of 2D-MoNx provides new nanostructures to optimize the sulfur redox chemistry and eliminate the shuttle effect of polysulfides.

Abnormal stability of spontaneous neuronal activity as a predictor of diagnosis conversion from major depressive disorder to bipolar disorder

OBJECTIVE

Bipolar disorder (BD) is often misdiagnosed as major depressive disorder (MDD) in the early stage, which may lead to inappropriate treatment. This study aimed to characterize the alterations of spontaneous neuronal activity in patients with depressive episodes whose diagnosis transferred from MDD to BD.

METHODS

532 patients with MDD and 132 healthy controls (HCs) were recruited over 10 years. During the follow-up period, 75 participants with MDD transferred to BD (tBD), and 157 participants remained with the diagnosis of unipolar depression (UD). After excluding participants with poor image quality and excessive head movement, 68 participants with the diagnosis of tBD, 150 participants with the diagnosis of UD, and 130 HCs were finally included in the analysis. The dynamic amplitude of low-frequency fluctuations (dALFF) of spontaneous neuronal activity was evaluated in tBD, UD and HC using functional magnetic resonance imaging at study inclusion. Receiver operating characteristic (ROC) analysis was performed to evaluate sensitivity and specificity of the conversion prediction from MDD to BD based on dALFF.

RESULTS

Compared to HC, tBD exhibited elevated dALFF at left premotor cortex (PMC_L), right lateral temporal cortex (LTC_R) and right early auditory cortex (EAC_R), and UD showed reduced dALFF at PMC_L, left paracentral lobule (PCL_L), bilateral medial prefrontal cortex (mPFC), right orbital frontal cortex (OFC_R), right dorsolateral prefrontal cortex (DLPFC_R), right posterior cingulate cortex (PCC_R) and elevated dALFF at LTC_R. Furthermore, tBD exhibited elevated dALFF at PMC_L, PCL_L, bilateral mPFC, bilateral OFC, DLPFC_R, PCC_R and LTC_R than UD. In addition, ROC analysis based on dALFF in differential areas obtained an area under the curve (AUC) of 72.7%.

CONCLUSIONS

The study demonstrated the temporal dynamic abnormalities of tBD and UD in the critical regions of the somatomotor network (SMN), default mode network (DMN), and central executive network (CEN). The differential abnormal patterns of temporal dynamics between the two diseases have the potential to predict the diagnosis transition from MDD to BD.

Perioperative Vision Loss Following Prone Spine Surgery: A Case-Control Study

PURPOSE

Perioperative vision loss (POVL) is a rare and devastating complication following prone spine surgery. Due to the rare nature of this complication, there is limited research available about patient and surgical risk factors that increase the risk of POVL. The objective of this study was to investigate associated risk factors for POVL with use of the National Surgical Quality Improvement Program (NSQIP) database.

DESIGN

This study used a case-control secondary data analysis methodology that included five cases of POVL and 250 controls from the American College of Surgeons National Surgical Quality Improvement Program database who all underwent prone spine surgery between 2010 and 2020.

METHODS

Each POVL case was matched to 50 randomly selected controls (n = 250) based on type and year of surgery. Demographics and variables of interest were compared among the POVL cases, among POVL cases and the aggregate control group (n = 250), and POVL cases against their matched control group. Univariate and multivariate conditional logistic regression were then used to estimate the odds of developing POVL in relation to potential patient and surgical risk factors.

FINDINGS

When POVL cases were compared to the 250 control cases using univariate analysis, patients who developed POVL were more likely to have received a blood transfusion within 72 hours of surgery (P < .0001). and have longer operative times (odds ratio = 1.01, 95% CI [1.003, 1.017], P = .003).

CONCLUSIONS

Two surgical risk factors were determined to be statistically significant, including the need for perioperative blood transfusion and prolonged operative time. These findings support previous research on POVL which often identified blood loss and prolonged operative times as surgical risk factors. The narrow patient population used in this project may have limited the ability to perform a more robust study on POVL. Therefore, further research on POVL using the National Surgical Quality Improvement Program database is strongly encouraged.

Microstructural and functional alterations of the ventral pallidum are associated with levodopa-induced dyskinesia in Parkinson's disease

BACKGROUND AND PURPOSE

The ventral pallidum (VP) regulates involuntary movements, but it is unclear whether the VP regulates the abnormal involuntary movements in Parkinson's disease (PD) patients who have levodopa-induced dyskinesia (LID). To further understand the role of the VP in PD patients with LID (PD-LID), we explored the structural and functional characteristics of the VP in such patients using multimodal magnetic resonance imaging (MRI).

METHODS

Thirty-one PD-LID patients, 39 PD patients without LID (PD-nLID), and 28 healthy controls (HCs) underwent T1-weighted MRI, quantitative susceptibility mapping, multi-shell diffusion MRI, and resting-state functional MRI (rs-fMRI). Different measures characterizing the VP were obtained using a region-of-interest-based approach.

RESULTS

The left VP in the PD-LID group showed significantly higher intracellular volume fraction (ICVF) and isotropic volume fraction (IsoVF) compared with the PD-nLID and HC groups. Rs-MRI revealed that, compared with the PD-nLID group, the PD-LID group in the medication 'off' state had higher functional connectivity (FC) between the left VP and the left anterior caudate, left middle frontal gyrus and left precentral gyrus, as well as between the right VP and the right posterior ventral putamen and right mediodorsal thalamus. In addition, the ICVF values of the left VP, the FC between the left VP and the left anterior caudate and left middle frontal gyrus were positively correlated with Unified Dyskinesia Rating Scale scores.

CONCLUSION

Our multimodal imaging findings show that the microstructural changes of the VP (i.e., the higher ICVF and IsoVF) and the functional change in the ventral striatum-VP-mediodorsal thalamus-cortex network may be associated with pathophysiological mechanisms of PD-LID.

Bioactivities and Structure-Activity Relationships of Maslinic Acid Derivatives: A Review

Maslinic acid has a variety of biological activities, such as anti-tumor, hypoglycemic, anti-inflammatory, and anti-parasitic. In order to enhance the biological activity of maslinic acid, scholars have carried out a lot of structural modifications, and found some more valuable maslinic acid derivatives. In this paper, the structural modification, biological activity, and structure-activity relationship of maslinic acid were reviewed, providing references for the development of maslinic acid.

Transport and inhibition mechanisms of human VMAT2

Vesicular monoamine transporter 2 (VMAT2) accumulates monoamines in presynaptic vesicles for storage and exocytotic release, and has a vital role in monoaminergic neurotransmission1-3. Dysfunction of monoaminergic systems causes many neurological and psychiatric disorders, including Parkinson's disease, hyperkinetic movement disorders and depression4-6. Suppressing VMAT2 with reserpine and tetrabenazine alleviates symptoms of hypertension and Huntington's disease7,8, respectively. Here we describe cryo-electron microscopy structures of human VMAT2 complexed with serotonin and three clinical drugs at 3.5-2.8 Å, demonstrating the structural basis for transport and inhibition. Reserpine and ketanserin occupy the substrate-binding pocket and lock VMAT2 in cytoplasm-facing and lumen-facing states, respectively, whereas tetrabenazine binds in a VMAT2-specific pocket and traps VMAT2 in an occluded state. The structures in three distinct states also reveal the structural basis of the VMAT2 transport cycle. Our study establishes a structural foundation for the mechanistic understanding of substrate recognition, transport, drug inhibition and pharmacology of VMAT2 while shedding light on the rational design of potential therapeutic agents.

Evaluation of the Efficacy of a Lactobacilli-Based Teat Detergents for the Microbiota of Cows Teats Using an Untargeted Metabolomics Approach

Teat cleaning pre- and post-milking is important for the overall health and hygiene of dairy cows. The purpose of this research was to evaluate the effectiveness of a teat detergents based on lactic acid bacteria according to changes in somatic cell count and cow-milk metabolites. Sixty-nine raw milk samples were collected from 11 Holstein-Friesian cows in China during 12 days of teat cleaning. An ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry-based untargeted metabolomic approach was applied to detect metabolomic differences after treatment with lactic acid bacteria and chemical teat detergents in cows with subclinical mastitis. The results suggest that the lactobacilli-based teat detergents could reduce somatic cell count and improve microhabitat of cow teat apex by adjusting the composition of metabolites. Furthermore, the somatic cell count could be decreased significantly within 10 days following the cleaning protocol. Lactic acid bacteria have the potential to be applied as a substitution to teat chemical detergents before and after milking for maintenance of healthy teats and breasts. Further, larger scale validation work is required to support the findings of the current study.

Research on Time Series-Based Pipeline Ground Penetrating Radar Calibration Angle Prediction Algorithm

The pipeline ground-penetrating radar stands as an indispensable detection device for ensuring underground space security. A wheeled pipeline robot is deployed to traverse the interior of urban underground drainage pipelines along their central axis. It is subject to influences such as resistance, speed, and human factors, leading to deviations in its posture. A guiding wheel is employed to rectify its roll angle and ensure the precise spatial positioning of defects both inside and outside the pipeline, as detected by the radar antenna. By analyzing its deflection factors and correction trajectories, the intelligent correction control of the pipeline ground-penetrating radar falls into the realm of nonlinear multi-constraint optimization. Consequently, a time-series-based correction angle prediction algorithm is proposed. The application of the long short-term memory (LSTM) deep learning model facilitates the prediction of correction angles and torque for the guiding wheel. This study compares the performance of LSTM with an autoregressive integrated moving average model under identical dataset conditions. The subsequent findings reveal a reduction of 4.11° and 8.25 N·m in mean absolute error, and a decrease of 10.66% and 7.27% in mean squared error for the predicted correction angles and torques, respectively. These outcomes are achieved utilizing the three-channel drainage pipeline ground-penetrating radar device with top antenna operating at 1.2 GHz and left/right antennas at 750 MHz. The LSTM prediction model intelligently corrects its posture. Experimental results demonstrate an average correction speed of 5 s and an average angular error of ±1°. It is verified that the model can correct its attitude in real-time with small errors, thereby enhancing the accuracy of ground-penetrating radar antennas in locating pipeline defects.

Auto-suppression of Tet dioxygenases protects the mouse oocyte genome from oxidative demethylation

DNA cytosine methylation plays a vital role in repressing retrotransposons, and such derepression is linked with developmental failure, tumorigenesis and aging. DNA methylation patterns are formed by precisely regulated actions of DNA methylation writers (DNA methyltransferases) and erasers (TET, ten-eleven translocation dioxygenases). However, the mechanisms underlying target-specific oxidation of 5mC by TET dioxygenases remain largely unexplored. Here we show that a large low-complexity domain (LCD), located in the catalytic part of Tet enzymes, negatively regulates the dioxygenase activity. Recombinant Tet3 lacking LCD is shown to be hyperactive in converting 5mC into oxidized species in vitro. Endogenous expression of the hyperactive Tet3 mutant in mouse oocytes results in genome-wide 5mC oxidation. Notably, the occurrence of aberrant 5mC oxidation correlates with a consequent loss of the repressive histone mark H3K9me3 at ERVK retrotransposons. The erosion of both 5mC and H3K9me3 causes ERVK derepression along with upregulation of their neighboring genes, potentially leading to the impairment of oocyte development. These findings suggest that Tet dioxygenases use an intrinsic auto-regulatory mechanism to tightly regulate their enzymatic activity, thus achieving spatiotemporal specificity of methylome reprogramming, and highlight the importance of methylome integrity for development.

Links among genetic variants and hierarchical brain structural and functional networks for antidepressant treatment: A multivariate study

BACKGROUND

Antidepressant treatment effects are strongly heritable and have substantial effects on brain function and structure, but the underlying mechanisms are still poorly understood. In this research, we aimed to evaluate the factors of single nucleotide polymorphisms (SNPs) and hierarchical brain structural and functional networks that were associated with antidepressant treatment. Moreover, we further explored the correlations and mediation pattern among "brain structure-brain function-gene" in major depressive disorder (MDD).

METHODS

We analysed 405 SNPs and rich club/feeder/local connections of hierarchical structural and functional networks with three-way parallel independent component analysis in 179 MDD patients. The group-discriminative independent components of the three modalities between responders and non-responders of antidepressant treatment were identified. Pearson correlations and mediation analysis were further utilized to investigate the associations among SNPs and connections of the structural and functional networks.

RESULTS

Notably, correlations with antidepressant treatment outcomes were found in structural, functional and SNP modalities simultaneously. The features of group-discriminative independent components included the shared feeder connections of hub regions with the inferior frontal orbital gyrus and amygdala in structural and functional modalities and genes enriched in circadian rhythmic processes and dopaminergic synapse pathways. The structural feeder network displayed close correlations with SNPs and the functional feeder network. Furthermore, the structural feeder network could mediate the association between SNPs and the functional feeder network, implying that genetic variants might influence brain function by affecting brain structure in MDD.

CONCLUSIONS

These findings provide potential biomarkers for antidepressant therapy and provide a better grasp of the associations among SNPs and hierarchical structural and functional networks in MDD.

Abnormal fractional amplitude of low-frequency fluctuations and regional homogeneity in major depressive disorder with non-suicidal self-injury

OBJECTIVE

We conducted this resting-state functional magnetic resonance imaging (rsfMRI) study to characterize changes in regional homogeneity (ReHo) or fractional amplitude of low-frequency fluctuations (fALFF) in young adult patients with major depressive disorder (MDD), with or without non-suicidal self-injury (NSSI).

METHODS

We recruited 54 MDD patients with NSSI (MDD/NSSI), 68 MDD patients without NSSI, which is referred to as simple MDD (sMDD), and 66 matched healthy controls (HCs). A combination of fALFF and ReHo analyses was conducted. The effects of NSSI on the brain and their relationship to clinical variables were examined in this study.

RESULTS

MDD/NSSI patients have decreased fALFF in the right superior frontal gyrus (SFG) and the right inferior parietal lobe (IPL), decreased ReHo in the right SFG and the right middle temporal gyrus (MTG) and the left middle occipital gyrus (MOG). fALFF and ReHo values of the right SFG are positively correlated. The ReHo values of the right SFG and the number of recent self-injuries are positively correlated; the fALFF values of the right SFG are negatively correlated with NSSI severity.

CONCLUSIONS

There is a difference in brain activity between MDD/NSSI and sMDD, which may serve as an important physiological marker to determine the risk of self-injury and suicide.

SIGNIFICANCE

Abnormal brain activity in patients with NSSI may provide new perspectives and significant implications on the severity of MDD patients and the prevention of self-injury and suicide.

Enhancing physiological recovery and subsequent exercise performance in the heat using a phase-change material cooling blanket

This study aimed to assess the effect of a phase-change material (PCM) cooling blanket for cooling between exercise bouts on recovery of physiological parameters and subsequent exercise performance in the heat. Eighteen male volunteers were recruited to participate in human trials involving two exhaustive treadmill running bouts (Bout1 for 3 km and Bout2 for 1.5 km) in a climate chamber (temperature = 33 °C; relative humidity = 40%). Participants were randomly subjected to one of two cooling conditions for a 10-min period between exercise bouts: CON: natural cooling; 10-min PCM: with a PCM cooling blanket for 10 min. Several physiological parameters including mean skin temperature (Tskin), oral temperature (Toral), core temperature (Tcore), heart rate (HR), mean arterial pressure (MAP), respiratory rate (RR), peripheral capillary oxygen saturation (SpO2), average running speed and rating of perceived exertion (RPE) scale score were analyzed. The results showed that compared to the CON group, participants in the 10-min PCM group had a significant lower Tskin, Tcore, HR and RR at post-cooling, as well as greater reductions in mean skin temperature (ΔTskin) and core temperature (ΔTcore) from post-Bout1 to post-cooling. Additionally, the 10-min PCM group exhibited significantly lower peak Tcore, peak HR and RPE scale score during Bout2, while the average running speed during Bout2 was significantly higher. The present study suggests that cooling with a PCM cooling blanket can enhance physiological recovery and subsequent exercise performance in the heat.

Iatrogenic flexor tendon rupture caused by misdiagnosing sarcoidosis-related flexor tendon contracture as tenosynovitis: A case report

BACKGROUND

Sarcoidosis is a multisystem disease characterized by granuloma formation in various organs. Sarcoidosis-related flexor tendon contractures are uncommon in clinical settings. This contracture is similar to stenosing tenosynovitis and potentially leads to misdiagnosis and mistreatment. Herein, we report a rare case of sarcoidosis-related finger flexor tendon contracture that was misdiagnosed as tenosynovitis.

CASE SUMMARY

A 44-year-old woman presented to our department with flexion contracture of the right ring and middle fingers. The patient was misdiagnosed with tenosynovitis and underwent acupotomy release of the A1 pulley of the middle finger in another hospital that resulted in iatrogenic rupture of both the superficial and profundus flexors. Radiological presentation showed multiple sarcoid involvements in the pulmonary locations and ipsilateral forearm. A diagnosis of sarcoidosis was made based on the presence of non-caseating granulomas with tubercles consisting of Langhans giant cells with lymphocyte infiltration on biopsy, and the patient underwent surgical repair for the contracture. After 2 mo, the patient experienced another spontaneous rupture of the repaired middle finger tendon and underwent surgical re-repair. Satisfactory results were achieved at the 10 mo follow-up after reoperation.

CONCLUSION

Sarcoidosis-related finger contractures are rare; thus, caution should be exercised when dealing with such patients to avoid incorrect treatment.

Acceptance of the Human Papillomavirus Vaccine among General Men and Men with a Same-Sex Orientation and Its Influencing Factors: A Systematic Review and Meta-Analysis

The human papillomavirus (HPV) vaccine reduces the prevalence of genital warts and the cancers they are associated with in males. However, the vaccination of males has always been neglected. Here, we performed a meta-analysis to comprehend the acceptability of the HPV vaccine in men and the factors impacting vaccination intentions. We searched PubMed, Web of Science, Embase, Ovid, CNKI, and Wan Fang up to 5 July 2023 for studies that reported HPV vaccine acceptance among men. A random effects model was used to obtain the pooled acceptance rate, and subgroup analysis was performed. Then, the influencing factors of HPV vaccination in males were analyzed. A total of 57 studies with 32,962 samples were included in the analysis. The overall acceptance rate of the HPV vaccine in general men was 47.04% (95% confidence interval [95%CI]: 39.23-54.93%), and 62.23% (95% CI: 52.93-71.10%) among those whose sexual orientation contained men. HPV vaccine acceptance rates differed significantly between the two populations (p = 0.01). The population with a medical background (46.23%, 95% CI: 40.28-52.24%) was more willing to be vaccinated. In comparison to the employed population (66.93%, 95% CI: 48.79-82.81%) and the unemployed (68.44%, 95% CI: 52.82-82.23%), vaccination acceptance rates were lower among students (47.35%, 95% CI: 37.00-57.81%) (p = 0.04). The most significant barriers to vaccination were perceived low risk of infection for themselves (45.91%, 95% CI: 31.73-60.43%), followed by vaccine cost (43.46%, 95% CI: 31.20-56.13%). Moreover, the recommendations from medical professionals (60.90%, 95%CI: 44.23-76.37%) and sexual partners (60.09%, 95%CI: 27.11-88.67%) were significant factors in promoting vaccination. Overall, acceptance of the HPV vaccine among general men was at a lower level, despite being slightly higher among men with a same-sex orientation. Popularizing knowledge about diseases and vaccines, encouraging medical professionals to recommend vaccines to men, or reducing the cost of vaccines may promote HPV vaccination.

Semantic-Disentangled Transformer With Noun-Verb Embedding for Compositional Action Recognition

Recognizing actions performed on unseen objects, known as Compositional Action Recognition (CAR), has attracted increasing attention in recent years. The main challenge is to overcome the distribution shift of "action-objects" pairs between the training and testing sets. Previous works for CAR usually introduce extra information (e.g. bounding box) to enhance the dynamic cues of video features. However, these approaches do not essentially eliminate the inherent inductive bias in the video, which can be regarded as the stumbling block for model generalization. Because the video features are usually extracted from the visually cluttered areas in which many objects cannot be removed or masked explicitly. To this end, this work attempts to implicitly accomplish semantic-level decoupling of "object-action" in the high-level feature space. Specifically, we propose a novel Semantic-Decoupling Transformer framework, dubbed as DeFormer, which contains two insightful sub-modules: Objects-Motion Decoupler (OMD) and Semantic-Decoupling Constrainer (SDC). In OMD, we initialize several learnable tokens incorporating annotation priors to learn an instance-level representation and then decouple it into the appearance feature and motion feature in high-level visual space. In SDC, we use textual information in the high-level language space to construct a dual-contrastive association to constrain the decoupled appearance feature and motion feature obtained in OMD. Extensive experiments verify the generalization ability of DeFormer. Specifically, compared to the baseline method, DeFormer achieves absolute improvements of 3%, 3.3%, and 5.4% under three different settings on STH-ELSE, while corresponding improvements on EPIC-KITCHENS-55 are 4.7%, 9.2%, and 4.4%. Besides, DeFormer gains state-of-the-art results either on ground-truth or detected annotations.

Migration and adsorption of naphthalene in road-deposited sediments from stormwater runoff: Impact of the particle size

In this study, we explored the impact of RDS particle size on the migration dynamics of RDS and naphthalene through rigorous wash-off experiments. The results illuminated that smaller RDS particles showed higher mobility in stormwater runoff. On the other hand, RDS particles larger than 150 μm showed migration ratios below 2 %, suggesting that naphthalene adsorbed on larger RDS primarily migrated in dissolved form. Furthermore, we investigated the migration behaviors of RDS and naphthalene under varied conditions, including rainfall intensity, duration, and naphthalene concentrations. Larger rainfall intensity promoted the naphthalene release from RDS, while long rainfall duration (≥10 min) impeded the migration velocities (≤2.91 %/5 min for RDS, and ≤3.32 %/5 min for corresponding naphthalene) of RDS and naphthalene. Additionally, higher naphthalene concentrations in RDS diminished migration ratios of dissolved naphthalene. Significantly, the maximum uptake of naphthalene on RDS was 6.02 mg/g by the adsorption Langmuir isotherm. Importantly, the adsorption process of naphthalene in RDS is primarily governed by the physical adsorption, as demonstrated by the successive desorption experiments, which showed the desorption rate of up to 87.32 %. Moreover, advanced characterizations such as XPS, FTIR and Raman spectra further confirmed the physical nature of the adsorption process. These findings may help the understanding of the migration behavior of other pollutants in urban surface particulates.

Toward High-Accuracy and Low-Latency Spiking Neural Networks With Two-Stage Optimization

Spiking neural networks (SNNs) operating with asynchronous discrete events show higher energy efficiency with sparse computation. A popular approach for implementing deep SNNs is artificial neural network (ANN)-SNN conversion combining both efficient training of ANNs and efficient inference of SNNs. However, the accuracy loss is usually nonnegligible, especially under few time steps, which restricts the applications of SNN on latency-sensitive edge devices greatly. In this article, we first identify that such performance degradation stems from the misrepresentation of the negative or overflow residual membrane potential in SNNs. Inspired by this, we decompose the conversion error into three parts: quantization error, clipping error, and residual membrane potential representation error. With such insights, we propose a two-stage conversion algorithm to minimize those errors, respectively. In addition, we show that each stage achieves significant performance gains in a complementary manner. By evaluating on challenging datasets including CIFAR-10, CIFAR-100, and ImageNet, the proposed method demonstrates the state-of-the-art performance in terms of accuracy, latency, and energy preservation. Furthermore, our method is evaluated using a more challenging object detection task, revealing notable gains in regression performance under ultralow latency, when compared with existing spike-based detection algorithms. Codes will be available at: https://github.com/Windere/snn-cvt-dual-phase.