The effectiveness of digital interactive intervention on reducing older adults' depressive and anxiety symptoms: A systematic review and meta-analysis.

INTRODUCTION: Anxiety and depression are prevalent among older adults, and digital interactive interventions have shown promise in promoting their mental well-being. However, limited research has explored the effects of different types of digital interactive interventions across various devices on anxiety and depression in older adults with different health conditions. METHODS: A systematic literature review and meta-analysis were conducted using seven selected databases to identify relevant studies up to July 19, 2023. Two reviewers independently conducted study selection, data extraction, and quality appraisals. The risk of bias in the included studies was assessed using the Cochrane risk-of-bias tool. For the meta-analysis, the effect size was calculated as the standardized mean difference (SMD) using a random effects model. RESULTS: A total of 20 randomized control trails involving 1309 older adults fulfilled inclusion criteria. The meta-analysis results demonstrates that the digital interactive intervention technologies had a significance on Depression (SMD = -0.656 s, 95% CI = -0.992 to -0.380, P < 0.001) and Anxiety (SMD = -0.381s, 95% CI = -0.517 to -0.245, P < 0.001). Physical Interactive interventions demonstrated a significant effect on depression and anxiety (SMD = -0.711s, 95% CI = -1.102 to -0.319, P < 0.001) and (SMD = -0.573s, 95% CI = -0.910 to -0.236, P = 0.001). Similarly, Immersive Interactive interventions also showed a significant effect on depression and anxiety (SMD = -0.699s, 95% CI = -1.026 to -0.373, P < 0.001) and (SMD = -0.343s, 95% CI = -0.493 to -0.194, P < 0.001). Additionally, in the Internal Medicine group, significant intervention effects were observed for depression (SMD = -0.388, 95% CI = -0.630 to -0.145, P = 0.002) and anxiety (SMD = -0.325, 95% CI = -0.481 to -0.169, P < 0.001). Similarly, in the Neurocognitive Disorders group, significant intervention effects were found for depression (SMD = -0.702, 95% CI = -0.991 to -0.413, P < 0.001) and anxiety (SMD = -0.790, 95% CI = -1.237 to -0.342, P = 0.001). CONCLUSION: The results indicated that various digital interactive devices, including physical and immersive interactive devices, have a positive impact on depression and anxiety among older adults. However, mobile games were not effective in addressing depression. Digital interactive technologies did not significantly influence anxiety intervention, except for elderly individuals undergoing surgical procedures. Nevertheless, these interventions effectively addressed depression and anxiety in older individuals with neurocognitive disorders, internal medical issues, and those without health issues.

What Is the Real-life Experience of Older Adults on Smart Healthcare Technologies? An Exploratory Interview Study.

INTRODUCTION: Smart healthcare technologies exhibit the great potential to support older Hong Kong adults with their health problems. Although there are various smart healthcare technologies in the Hong Kong market, and some adoption predictors have been proposed and investigated, little is known about older users' views on and real-life experiences with these technologies. This exploratory study examined the experiences, functional needs and barriers of three kinds of smart healthcare technology (i.e., smart wearable devices, smart health monitors, and healthcare applications) with older adults in real-life. METHODS: A convenience sampling method was applied to recruit twenty-two older adults from the Hong Kong community. The interview was designed in semi-structured and conducted in a face-to-face setting. The content analysis was used to summarize the older adults' functional needs and barriers in real-life. RESULTS: We found older adults mainly applied SHCTs to address physical health, but there are few technological solutions for mental health in practice. There are four types of barriers in using smart healthcare technology. However, social support in Hong Kong community greatly help to reduce the barriers in technology use. Based on the findings, we discussed the possible solutions based on the social and technology perspective. CONCLUSION: Current technologies still could not fully address older adults needs for healthy aging and various barriers still hinder the actual adoption. By deeply understanding and considering the social context, technology innovation can facilitate the adoption of smart healthcare technology and promote a healthy aging society.

Effectiveness of sensor-based interventions in improving gait and balance performance in older adults: systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Sensor-based interventions (SI) have been suggested as an alternative rehabilitation treatment to improve older adults' functional performance. However, the effectiveness of different sensor technologies in improving gait and balance remains unclear and requires further investigation. METHODS: Ten databases (Academic Search Premier; Cumulative Index to Nursing and Allied Health Literature, Complete; Cochrane Central Register of Controlled Trials; MEDLINE; PubMed; Web of Science; OpenDissertations; Open grey; ProQuest; and Grey literature report) were searched for relevant articles published up to December 20, 2022. Conventional functional assessments, including the Timed Up and Go (TUG) test, normal gait speed, Berg Balance Scale (BBS), 6-Minute Walk Test (6MWT), and Falling Efficacy Scale-International (FES-I), were used as the evaluation outcomes reflecting gait and balance performance. We first meta-analyzed the effectiveness of SI, which included optical sensors (OPTS), perception sensors (PCPS), and wearable sensors (WS), compared with control groups, which included non-treatment intervention (NTI) and traditional physical exercise intervention (TPEI). We further conducted sub-group analysis to compare the effectiveness of SI (OPTS, PCPS, and WS) with TPEI groups and compared each SI subtype with control (NTI and TPEI) and TPEI groups. RESULTS: We scanned 6255 articles and performed meta-analyses of 58 selected trials (sample size = 2713). The results showed that SI groups were significantly more effective than control or TPEI groups (p < 0.000) in improving gait and balance performance. The subgroup meta-analyses between OPTS groups and TPEI groups revealed clear statistically significant differences in effectiveness for TUG test (mean difference (MD) = - 0.681 s; p < 0.000), normal gait speed (MD = 4.244 cm/s; p < 0.000), BBS (MD = 2.325; p = 0.001), 6MWT (MD = 25.166 m; p < 0.000), and FES-I scores (MD = - 2.036; p = 0.036). PCPS groups also presented statistically significant differences with TPEI groups in gait and balance assessments for normal gait speed (MD = 4.382 cm/s; p = 0.034), BBS (MD = 1.874; p < 0.000), 6MWT (MD = 21.904 m; p < 0.000), and FES-I scores (MD = - 1.161; p < 0.000), except for the TUG test (MD = - 0.226 s; p = 0.106). There were no statistically significant differences in TUG test (MD = - 1.255 s; p = 0.101) or normal gait speed (MD = 6.682 cm/s; p = 0.109) between WS groups and control groups. CONCLUSIONS: SI with biofeedback has a positive effect on gait and balance improvement among a mixed population of older adults. Specifically, OPTS and PCPS groups were statistically better than TPEI groups at improving gait and balance performance, whereas only the group comparison in BBS and 6MWT can reach the minimal clinically important difference. Moreover, WS groups showed no statistically or clinically significant positive effect on gait and balance improvement compared with control groups. More studies are recommended to verify the effectiveness of specific SI. Research registration PROSPERO platform: CRD42022362817. Registered on 7/10/2022.

of Potential Noncoding RNAs Related to Spinal Cord Injury Based on Competing Endogenous RNAs.

This study aims to elucidate the key regulatory molecules, specifically messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and microRNAs (miRNAs) and their roles in the development and progression of spinal cord injury (SCI). Expression profiles (GSE45006, GSE19890, and GSE125630) for SCI were sourced from the Gene Expression Omnibus (GEO) database. By comparing rats with SCI at various time points against those without SCI, we identified differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs). The GSE45006 dataset facilitated the production of DEmRNAs, which were then clustered using Mfuzz. Subsequently, we constructed a protein-protein interaction (PPI) network and anticipated interaction pairs between miRNA-mRNA and lncRNA-mRNA. These pairs were instrumental in forming a regulatory network involving lncRNA-miRNA-mRNA interactions. Additionally, we conducted functional enrichment studies on the DEmRNAs within these gene networks. A total of 2313 DEmRNAs were identified using the GSE45006 dataset, alongside 111 DEmiRNAs from GSE19890. From GSE125630, we extracted 154 DElncRNAs and 2322 DEmRNAs. Our analysis revealed 294 up-regulated DEmRNAs, grouped into the up-cluster, and 407 down-regulated DEmRNAs, forming the down-cluster. Key hub genes in the PPI network, such as Rhof, Vav1, Lyz2, Rab3a, Lyn, Cyfip1, Gns, and Nckap1l, were identified. Additionally, the study successfully constructed a competing endogenous RNA (ceRNA) network, revealing 55 unique lncRNA-miRNA-mRNA link pairs. Our research established a ceRNA network associated with SCI, identifying several critical lncRNA-miRNA-mRNA connection pairs integral to the disease's onset and progression. Notably, significant associations, including the AABR07041411.1-miR-125a-5p-Slc4a7 and the Smg1-rno-miR-331-3p-Tlr4 pairs, were observed to exert a significant influence within this biological context.

In Situ Generated CO Enables High-Current CO2 Reduction to Methanol in a Molecular Catalyst Layer.

Molecular catalysts such as cobalt phthalocyanine (CoPc) exhibit remarkable electrochemical activity in methanol production from CO2 or CO, but fast conversion with a high current density is still yet to be realized. While adopting flow cells with gas diffusion electrodes is a common approach to enhanced reaction rates, the current scientific and engineering knowledge primarily centers on metal particle-based catalysts like Cu. This focus overlooks the emerging heterogenized molecular catalysts with distinct physical and chemical properties. In this work, we observe that the partial current density of CO reduction to methanol catalyzed by tetraamine-substituted CoPc (CoPc-NH2) supported on carbon nanotubes (CNTs) remains below 30 mA cm-2, even with systematic optimization of structural and operational parameters of the flow cell. A comparative analysis with a Cu metal catalyst reveals that the porous and electrolyte-philic nature of CoPc-NH2/CNT leaves a large fraction of active sites deprived of CO under reaction conditions. To address this microenvironmental challenge, we directly use CO2 as the reactant, leveraging its faster diffusion rate in water compared to CO. Effective CO2 reduction generates CO in situ to feed the catalytic sites, achieving an unprecedently high partial current density for methanol of 129 mA cm-2. This research underscores the necessity for new insights and approaches in the development of molecular catalyst-based electrodes.

Digital Behavior Change Intervention Designs for Habit Formation: Systematic Review.

BACKGROUND: With the development of emerging technologies, digital behavior change interventions (DBCIs) help to maintain regular physical activity in daily life. OBJECTIVE: To comprehensively understand the design implementations of habit formation techniques in current DBCIs, a systematic review was conducted to investigate the implementations of behavior change techniques, types of habit formation techniques, and design strategies in current DBCIs. METHODS: The process of this review followed the PRISMA (Preferred Reporting Item for Systematic Reviews and Meta-Analyses) guidelines. A total of 4 databases were systematically searched from 2012 to 2022, which included Web of Science, Scopus, ACM Digital Library, and PubMed. The inclusion criteria encompassed studies that used digital tools for physical activity, examined behavior change intervention techniques, and were written in English. RESULTS: A total of 41 identified research articles were included in this review. The results show that the most applied behavior change techniques were the self-monitoring of behavior, goal setting, and prompts and cues. Moreover, habit formation techniques were identified and developed based on intentions, cues, and positive reinforcement. Commonly used methods included automatic monitoring, descriptive feedback, general guidelines, self-set goals, time-based cues, and virtual rewards. CONCLUSIONS: A total of 32 commonly design strategies of habit formation techniques were summarized and mapped to the proposed conceptual framework, which was categorized into target-mediated (generalization and personalization) and technology-mediated interactions (explicitness and implicitness). Most of the existing studies use the explicit interaction, aligning with the personalized habit formation techniques in the design strategies of DBCIs. However, implicit interaction design strategies are lacking in the reviewed studies. The proposed conceptual framework and potential solutions can serve as guidelines for designing strategies aimed at habit formation within DBCIs.

Dual-template synthesis of SFO-type aluminophosphate with enhanced water-sorption-driven cooling performance.

Water-based adsorption chillers (ADC) driven by low-grade thermal energy are environment-friendly alternatives to the traditional compression ones to realize the net zero carbon target. Aluminophosphates molecular sieve (AlPOs) is an excellent material for water-based adsorption applications. However, AlPOs suffers from relatively high cost attributed to the extensive use of expensive structure direct agents (SDAs). This study employed a dual-template method, using cheap organic amine as a dual-template, to synthesize low-cost and excellent adsorbent AlPOs with SFO topology (AlPO-SFO). AlPO-SFO synthesized with dual templates shows high crystallinity, large micropore volume, excellent water uptake, and low regeneration temperature. AlPO-SFO guided by 4-dimethylaminopyridine (4-DMAPy) and diethanolamine (DEOA) molar composition of 0.4 and 0.1 exhibits large microporous volume (0.30 ml g-1), high water uptake (0.26 g g-1 at P/P0 = 0.25) and low regeneration temperature (65 °C). Importantly, this AlPO-SFO exhibits a high coefficient of performance (COP) of 0.89 for cooling at a low driven temperature of 64 °C. The additive amine providing alkaline medium ensures the practical synthesis of AlPO-SFO when expensive 4-DMAPy decreases, endowing the 42 % reduction of the raw material cost. The results provide a cheaper synthesis route of AlPO-SFO, which is conducive to its large-scale production as a distinguished adsorbent for adsorption chillers.

Genome-based characterization of a novel prophage of Vibrio parahaemolyticus, VPS05ph1, a novel member of Peduoviridae.

Vibrio parahaemolyticus is a globally important bacterium related to climate warming and health threat to human and marine animals. Yet, there is limited knowledge about its polylysogeny harboring multiple prophages and the genetic information. In this study, two prophages (VPS05ph1 and VPS05ph2) were identified in a V. parahaemolyticus isolate through genomic and transcriptional analyses. Both prophages were determined as HP1-like phages, located in a novel phylogenetic lineage of Peduoviridae. They shared a moderate genome-wide sequence similarity with each other and high synteny with the closest relatives, but showed low identities to the repressor counterparts of the representative phages within the family. In addition, no bacterial virulence genes, antibiotic resistance genes and known phage-encoded lytic proteins were identified on both prophage genomes. Moreover, the V. parahaemolyticus isolate was induced with mitomycin, which caused aberrant cellular morphology and nonviability of bacterial cells and excision of prophage VPS05ph1, accompanied by the respective inhibition and promotion of transcriptions of the cI-like and cox-like regulator genes for phage decision making. Results in this study provide the genetic context of polylysogeny in the V. parahaemolyticus isolate, support the diversity and prevalence of HP1-like phages in vibrios, and promote to explore interactions between the HP1-like prophage and its vibrio host.

CO2-Promoted Electrocatalytic Reduction of Chlorinated Hydrocarbons.

Electrochemical reactions and their catalysis are important for energy and environmental applications, such as carbon neutralization and water purification. However, the synergy in electrocatalysis between CO2 utilization and wastewater treatment has not been explored. In this study, we find that the electrochemical reduction of chlorinated organic compounds such as 1,2-dichloroethane, trichloroethylene, and tetrachloroethylene into ethylene in aqueous media, which is a category of challenging reactions due to the competition of H2 evolution, can be substantially enhanced by simultaneously carrying out the reduction of CO2 on an easily prepared and cost-effective Cu metal catalyst. In the case of 1,2-dichloroethane dechlorination, a 6-fold improvement in Faradaic efficiency and a 19-fold increase in partial current density are demonstrated. Through electrochemical kinetic studies, in situ Raman spectroscopy, and computational simulations, we further find that CO2 reduction reduces hydrogen coverage on the Cu catalyst, which not only exposes more active sites for the dechlorination reaction but also enhances the effective reductive potential on the catalyst surface and reduces the kinetic barrier of the rate-determining step.

Prognostic significance of glucose-lipid metabolic index in pancreatic cancer patients with diabetes mellitus.

BACKGROUND: The incidence of pancreatic cancer (PC) is higher in diabetic patients due to disturbances in glucose and lipid metabolism caused by insulin resistance (IR). However, the effect of diabetes as well as IR on the prognosis of PC patients remains inconclusive. Our study aims to assess the impact of IR on the prognosis of PC patients with diabetes. METHODS: We conducted a retrospective analysis of 172 PC patients with diabetes in our institute from 2015 to 2021. Prognostic assessment was performed using univariate/multifactorial analysis and survival analysis. The predictive efficacy of metabolic indices was compared using receiver operator characteristic (ROC) curve analysis. RESULTS: One hundred twenty-one of 172 patients died during follow-up, with a median follow-up of 477 days and a median overall survival (OS) of 270 days. Survival analysis showed a significant difference in OS by IR related parameters, which were triglyceride-glucose index (TyG), triglyceride-glucose index-body mass index (TyG-BMI), and triglyceride/high-density lipoprotein cholesterol ratio (TG/HDL-c). The ROC curve indicated that TyG, TyG-BMI, and TG/HDL-c had prognostic efficacy for PC with diabetes. We next optimized TyG-BMI and obtained a new parameter, namely glucose-lipid metabolism index (GLMI), and the patients were classified into GLMI low group and high group based on the calculated cutoff value. The GLMI high group had higher TyG, TyG-BMI, TyG/HDL-c, BMI, TG, total cholesterol (TC), TC/HDL-c, fasting plasma glucose, CA199, and more advanced tumor stage compared to low group. Univariate and multivariate analyses showed that GLMI was an independent prognostic factor. Furthermore, the patients of GLMI high group had worse OS compared to low group and the ROC curves showed GLMI had better predictive ability than TyG and TyG-BMI. CONCLUSIONS: IR is associated with the outcome of PC patients with diabetes and higher level of IR indicates worse prognosis. GLMI has a good predictive value for PC with diabetes.

Differential Microbial Composition and Interkingdom Interactions in the Intestinal Microbiota of Holstein and German Simmental × Holstein Cross F1 Calves: A Comprehensive Analysis of Bacterial and Fungal Diversity.

Calf intestines are colonized by rich and complex microbial communities, playing a crucial role in animal physiology, metabolism, nutrition, and immune function. In this study, we provide insight into the composition of fecal microbial bacteria and fungi, respectively, as well as the cross-kingdom interactions. We investigated the intestinal microbiota of different breeds of calves by characterizing the bacterial and fungal communities in the rectal feces of Holstein calves and German Simmental × Holstein cross F1 generation (GXH) using 16S rRNA and ITS amplicon sequencing techniques. PICRUSt2 (version 2.2.0) were used to determine microbial diversity and function and explore the reasons why Holstein calves are more susceptible to diarrhea. The results revealed no significant difference in the diversity of fecal microbiota among the groups (p > 0.05). We identified Firmicutes, Bacteroidetes, and Proteobacteria as the dominant bacterial phyla in the fecal bacterial communities of the two breeds of calves. Ascomycota and Basidiomycota play important roles in the fungal community but differ in relative abundance. Bacteroides was the dominant genus at the group level for calf fecal microbiota in both breeds. The relative abundance of Prevotella, Escherichia-Shigella, Peptostreptococcus, and Butyricicoccus was higher in Holstein calves, and the relative abundance of Faecalibacterium, Megamonas, Butyricicoccus, and Alloprevotella was lower than GXH group. Aspergillus and Cladosporium were the dominating genera of fecal fungi in both groups of calves. LEfSe analysis revealed 33 different bacteria and 23 different fungi between the two groups, with more differential strains found in GXH. In addition, the feces fungi-bacteria interkingdom interactions varied among breeds. Thus, the composition and structure of bacterial and fungal communities in calf feces varied by breed, indicating a potential association between breed and microbial communities. We also found differences in the network between bacterial-fungal kingdoms. We explain the reasons for Holstein calves being more prone to diarrhea. This indicated that breed makes differences in calf diarrhea rates by influencing gut microbial composition and interactions.

Coordination of copper within a crystalline carbon nitride and its catalytic reduction of CO2.

Inherently disordered structures of carbon nitrides have hindered an atomic level tunability and understanding of their catalytic reactivity. Starting from a crystalline carbon nitride, poly(triazine imide) or PTI/LiCl, the coordination of copper cations to its intralayer N-triazine groups was investigated using molten salt reactions. The reaction of PTI/LiCl within CuCl or eutectic KCl/CuCl2 molten salt mixtures at 280 to 450 °C could be used to yield three partially disordered and ordered structures, wherein the Cu cations are found to coordinate within the intralayer cavities. Local structural differences and the copper content, i.e., whether full or partial occupancy of the intralayer cavity occurs, were found to be dependent on the reaction temperature and Cu-containing salt. Crystallites of Cu-coordinated PTI were also found to electrophoretically deposit from aqueous particle suspensions onto either graphite or FTO electrodes. As a result, electrocatalytic current densities for the reduction of CO2 and H2O reached as high as ∼10 to 50 mA cm-2, and remained stable for >2 days. Selectivity for the reduction of CO2 to CO vs. H2 increases for thinner crystals as well as for when two Cu cations coordinate within the intralayer cavities of PTI. Mechanistic calculations have also revealed the electrocatalytic activity for CO2 reduction requires a smaller thermodynamic driving force with two neighboring Cu atoms per cavity as compared to a single Cu atom. These results thus establish a useful synthetic pathway to metal-coordination in a crystalline carbon nitride and show great potential for mediating stable CO2 reduction at sizable current densities.

Identifying sensors-based parameters associated with fall risk in community-dwelling older adults: an investigation and interpretation of discriminatory parameters.

BACKGROUND: Falls pose a severe threat to the health of older adults worldwide. Determining gait and kinematic parameters that are related to an increased risk of falls is essential for developing effective intervention and fall prevention strategies. This study aimed to investigate the discriminatory parameter, which lay an important basis for developing effective clinical screening tools for identifying high-fall-risk older adults. METHODS: Forty-one individuals aged 65 years and above living in the community participated in this study. The older adults were classified as high-fall-risk and low-fall-risk individuals based on their BBS scores. The participants wore an inertial measurement unit (IMU) while conducting the Timed Up and Go (TUG) test. Simultaneously, a depth camera acquired images of the participants' movements during the experiment. After segmenting the data according to subtasks, 142 parameters were extracted from the sensor-based data. A t-test or Mann-Whitney U test was performed on the parameters for distinguishing older adults at high risk of falling. The logistic regression was used to further quantify the role of different parameters in identifying high-fall-risk individuals. Furthermore, we conducted an ablation experiment to explore the complementary information offered by the two sensors. RESULTS: Fifteen participants were defined as high-fall-risk individuals, while twenty-six were defined as low-fall-risk individuals. 17 parameters were tested for significance with p-values less than 0.05. Some of these parameters, such as the usage of walking assistance, maximum angular velocity around the yaw axis during turn-to-sit, and step length, exhibit the greatest discriminatory abilities in identifying high-fall-risk individuals. Additionally, combining features from both devices for fall risk assessment resulted in a higher AUC of 0.882 compared to using each device separately. CONCLUSIONS: Utilizing different types of sensors can offer more comprehensive information. Interpreting parameters to physiology provides deeper insights into the identification of high-fall-risk individuals. High-fall-risk individuals typically exhibited a cautious gait, such as larger step width and shorter step length during walking. Besides, we identified some abnormal gait patterns of high-fall-risk individuals compared to low-fall-risk individuals, such as less knee flexion and a tendency to tilt the pelvis forward during turning.

Spatially selective defect management of CsPbI3 films for high-performance carbon-based inorganic perovskite solar cells.

Defects formed at the surface, buried interface and grain boundaries (GB) of CsPbI3 perovskite films considerably limit photovoltaic performance. Such defects could be passivated effectively by the most prevalent post modification strategy without compromising the photoelectric properties of perovskite films, but it is still a great challenge to make this strategy comprehensive to different defects spatially distributed throughout the films. Herein, a spatially selective defect management (SSDM) strategy is developed to roundly passivate various defects at different locations within the perovskite film by a facile one-step treatment procedure using a piperazine-1,4-diium tetrafluoroborate (PZD(BF4)2) solution. The small-size PZD2+ cations could penetrate into the film interior and even make it all the way to the buried interface of CsPbI3 perovskite films, while the BF4- anions, with largely different properties from I- anions, mainly anchor on the film surface. Consequently, virtually all the defects at the surface, buried interface and grain boundaries of CsPbI3 perovskite films are effectively healed, leading to significantly improved film quality, enhanced phase stability, optimized energy level alignment and promoted carrier transport. With these films, the fabricated CsPbI3 PSCs based on carbon electrode (C-PSCs) achieve an efficiency of 18.27%, which is among the highest-reported values for inorganic C-PSCs, and stability of 500 h at 85 °C with 65% efficiency maintenance.

Identification and validation of stemness-based and ferroptosis-related molecular clusters in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with an extremely poor prognosis. Cancer stem cells (CSCs) are considered to be responsible for the poor survival, recurrence and therapy resistance of PDAC. Ferroptosis plays a crucial role in the sustain and survival of CSCs. Here, we employed a rigorous evaluation of multiple datasets to identify a novel stemness-based and ferroptosis-related genes (SFRGs) signature to access the potential prognostic application. This work we retrieved RNA-sequencing and clinical annotation data from the TCGA, ICGC, GTEx and GEO database, and acquired 26 stem cell gene sets and 259 ferroptosis genes from StemChecker database and FerrDb database, respectively. Based on consensus clustering and ssGSEA analysis, we identified two expression patterns of CSCs traits (C1 and C2). Then, WGCNA analysis was implemented to screen out hub module genes correlated with stemness. Furthermore, differential expression analysis, Pearson correlation analysis, and the Least absolute shrinkage and selection operator (LASSO) and Cox regression were performed to identify the SFRGs and to construct model. In addition, the differences in prognosis, tumor microenvironment (TME) components and therapy responses were evaluated between two risk groups. Finally, we verified the most influential marker ARNTL2 experimentally by western blot, qRT-PCR, sphere formation assay, mitoscreen assay, intracellular iron concentration determination and MDA determination assays. In conclusion, we developed a stemness-based and ferroptosis-related prognostic model, which could help predict overall survival for PDAC patients. Targeting ferroptosis may be a promising therapeutic strategy to inhibit PDAC progression by suppressing CSCs.

How Precisely Can Individual Molecules Be Analyzed? A Case Study on Locally Quantifying Forces and Energies Using Scanning Probe Microscopy.

Recent advances in scanning probe microscopy methodology have enabled the measurement of tip-sample interactions with picometer accuracy in all three spatial dimensions, thereby providing a detailed site-specific and distance-dependent picture of the related properties. This paper explores the degree of detail and accuracy that can be achieved in locally quantifying probe-molecule interaction forces and energies for adsorbed molecules. Toward this end, cobalt phthalocyanine (CoPc), a promising CO2 reduction catalyst, was studied on Ag(111) as a model system using low-temperature, ultrahigh vacuum noncontact atomic force microscopy. Data were recorded as a function of distance from the surface, from which detailed three-dimensional maps of the molecule's interaction with the tip for normal and lateral forces as well as the tip-molecule interaction potential were constructed. The data were collected with a CO molecule at the tip apex, which enabled a detailed visualization of the atomic structure. Determination of the tip-substrate interaction as a function of distance allowed isolation of the molecule-tip interactions; when analyzing these in terms of a Lennard-Jones-type potential, the atomically resolved equilibrium interaction energies between the CO tethered to the tip and the CoPc molecule could be recovered. Interaction energies peaked at less than 160 meV, indicating a physisorption interaction. As expected, the interaction was weakest at the aromatic hydrogens around the periphery of the molecule and strongest surrounding the metal center. The interaction, however, did not peak directly above the Co atom but rather in pockets surrounding it.

Tailoring Interfaces for Enhanced Methanol Production from Photoelectrochemical CO2 Reduction.

Efficient and stable photoelectrochemical reduction of CO2 into highly reduced liquid fuels remains a formidable challenge, which requires an innovative semiconductor/catalyst interface to tackle. In this study, we introduce a strategy involving the fabrication of a silicon micropillar array structure coated with a superhydrophobic fluorinated carbon layer for the photoelectrochemical conversion of CO2 into methanol. The pillars increase the electrode surface area, improve catalyst loading and adhesion without compromising light absorption, and help confine gaseous intermediates near the catalyst surface. The superhydrophobic coating passivates parasitic side reactions and further enhances local accumulation of reaction intermediates. Upon one-electron reduction of the molecular catalyst, the semiconductor-catalyst interface changes from adaptive to buried junctions, providing a sufficient thermodynamic driving force for CO2 reduction. These structures together create a unique microenvironment for effective reduction of CO2 to methanol, leading to a remarkable Faradaic efficiency reaching 20% together with a partial current density of 3.4 mA cm-2, surpassing the previous record based on planar silicon photoelectrodes by a notable factor of 17. This work demonstrates a new pathway for enhancing photoelectrocatalytic CO2 reduction through meticulous interface and microenvironment tailoring and sets a benchmark for both Faradaic efficiency and current density in solar liquid fuel production.

Insights into Materials, Physics, and Applications in Flexible and Wearable Acoustic Sensing Technology.

Sound plays a crucial role in the perception of the world. It allows to communicate, learn, and detect potential dangers, diagnose diseases, and much more. However, traditional acoustic sensors are limited in their form factors, being rigid and cumbersome, which restricts their potential applications. Recently, acoustic sensors have made significant advancements, transitioning from rudimentary forms to wearable devices and smart everyday clothing that can conform to soft, curved, and deformable surfaces or surroundings. In this review, the latest scientific and technological breakthroughs with insightful analysis in materials, physics, design principles, fabrication strategies, functions, and applications of flexible and wearable acoustic sensing technology are comprehensively explored. The new generation of acoustic sensors that can recognize voice, interact with machines, control robots, enable marine positioning and localization, monitor structural health, diagnose human vital signs in deep tissues, and perform organ imaging is highlighted. These innovations offer unique solutions to significant challenges in fields such as healthcare, biomedicine, wearables, robotics, and metaverse. Finally, the existing challenges and future opportunities in the field are addressed, providing strategies to advance acoustic sensing technologies for intriguing real-world applications and inspire new research directions.

Active Sites of Cobalt Phthalocyanine in Electrocatalytic CO2 Reduction to Methanol.

Many metal coordination compounds catalyze CO2 electroreduction to CO, but cobalt phthalocyanine hybridized with conductive carbon such as carbon nanotubes is currently the only one that can generate methanol. The underlying structure-reactivity correlation and reaction mechanism desperately demand elucidation. Here we report the first in situ X-ray absorption spectroscopy characterization, combined with ex situ spectroscopic and electrocatalytic measurements, to study CoPc-catalyzed CO2 reduction to methanol. Molecular dispersion of CoPc on CNT surfaces, as evidenced by the observed electronic interaction between the two, is crucial to fast electron transfer to the active sites and multi-electron CO2 reduction. CO, the key intermediate in the CO2 -to-methanol pathway, is found to be labile on the active site, which necessitates a high local concentration in the microenvironment to compete with CO2 for active sites and promote methanol production. A comparison of the electrocatalytic performance of structurally related porphyrins indicates that the bridging aza-N atoms of the Pc macrocycle are critical components of the CoPc active site that produces methanol. In situ X-ray absorption spectroscopy identifies the active site as Co(I) and supports an increasingly non-centrosymmetric Co coordination environment at negative applied potential, likely due to the formation of a Co-CO adduct during the catalysis.