Deciphering language disturbances in schizophrenia: A study using fine-tuned language models.

This research presents two stable language metrics, namely Successful Prediction Rate (SPR) and Disfluency (DF), to objectively quantify the linguistic disturbances associated with schizophrenia. These novel language metrics can capture both off-topic responses and incoherence in patients' speech by modeling speech information and fine-tuning techniques. Additionally, these metrics exhibit cultural sensitivity while providing a more comprehensive evaluation of linguistic abnormalities in schizophrenia. This research fine-tuned the ELECTRA Pretrained Language Model on a 750 MB text corpus obtained from major Chinese mental health forums. The effectiveness of the fine-tuned language model is verified on a group comprising 38 individuals diagnosed with schizophrenia and 25 meticulously matched healthy controls. The study explores the association between the fine-tuned language model and the Positive and Negative Syndrome Scale (PANSS) items. The results demonstrate that SPR is higher in healthy controls, indicating better language understanding by the pre-trained language model. Conversely, DF is higher in individuals with schizophrenia, indicating more inconsistent language structure. The relationship between linguistic features and P2 (conceptual disorganization) reveals that patients with positive P2 exhibit lower SPR and higher DF. Binary logistic regression using the combined SPR and DF features achieves 84.5 % accuracy in classifying P2, exceeding the performance of traditional features by 20.5 %. Moreover, the proposed linguistic features outperform traditional linguistic features in discriminating FTD (formal thought disorder), as demonstrated by multivariate linear regression analysis.

Validity, feasibility, and effectiveness of a voice-recognition based digital cognitive screener for dementia and mild cognitive impairment in community-dwelling older Chinese adults: A large-scale implementation study.

INTRODUCTION: We investigated the validity, feasibility, and effectiveness of a voice recognition-based digital cognitive screener (DCS), for detecting dementia and mild cognitive impairment (MCI) in a large-scale community of elderly participants. METHODS: Eligible participants completed demographic, cognitive, functional assessments and the DCS. Neuropsychological tests were used to assess domain-specific and global cognition, while the diagnosis of MCI and dementia relied on the Clinical Dementia Rating Scale. RESULTS: Among the 11,186 participants, the DCS showed high completion rates (97.5%) and a short administration time (5.9 min) across gender, age, and education groups. The DCS demonstrated areas under the receiver operating characteristics curve (AUCs) of 0.95 and 0.83 for dementia and MCI detection, respectively, among 328 participants in the validation phase. Furthermore, the DCS resulted in time savings of 16.2% to 36.0% compared to the Mini-Mental State Examination (MMSE) and Montral Cognitive Assessment (MoCA). DISCUSSION: This study suggests that the DCS is an effective and efficient tool for dementia and MCI case-finding in large-scale cognitive screening. HIGHLIGHTS: To our best knowledge, this is the first cognitive screening tool based on voice recognition and utilizing conversational AI that has been assessed in a large population of Chinese community-dwelling elderly. With the upgrading of a new multimodal understanding model, the DCS can accurately assess participants' responses, including different Chinese dialects, and provide automatic scores. The DCS not only exhibited good discriminant ability in detecting dementia and MCI cases, it also demonstrated a high completion rate and efficient administration regardless of gender, age, and education differences. The DCS is economically efficient, scalable, and had a better screening efficacy compared to the MMSE or MoCA, for wider implementation.

An Ultrahighly Stretchable and Recyclable Starch-Based Gel with Multiple Functions.

With the development of various gel-based flexible sensors, novel gels with multiple integrated and efficient properties, particularly recyclability, have been developed. Herein, a starch-based ADM (amylopectin (AP)-poly(3-[dimethyl-[2-(2-methylprop-2- enoyloxy)ethyl]azaniumyl]propane-1-sulfonate) (PDMAPS)-MXene) gel is prepared by a facile "cooking" strategy accompanying the gelatinization of AP and polymerization reaction of zwitterionic monomers. Reversible crosslinking in the gel occurs through hydrogen bonding and electrostatic interactions. The ADM gel exhibits high stretchability (≈2700%, after one month), swift self-healing performance, self-adhesive properties, favorable freezing resistance, and satisfactory moisturizing properties (≥30 days). Interestingly, the ADM gel can be recycled and reused by a "kneading" method and "dissolution-dialysis" process, respectively. Furthermore, the ADM gel can be assembled as a strain sensor with a broad working strain range (≈800%) and quick response time (response time 211 ms and recovery time 253 ms, under 10% strain) to detect various macro- and micro-human-motions, even under harsh conditions such as pronunciation and handwriting. The ADM gel can also be used as a humidity sensor to investigate humidity and human respiratory status, suggesting its practical application in personal health management. This study provides a novel strategy for the preparation of high-performance recycled gels and flexible sensors.

Electroactive Microorganisms in Advanced Energy Technologies.

Large-scale production of green and pollution-free materials is crucial for deploying sustainable clean energy. Currently, the fabrication of traditional energy materials involves complex technological conditions and high costs, which significantly limits their broad application in the industry. Microorganisms involved in energy production have the advantages of inexpensive production and safe process and can minimize the problem of chemical reagents in environmental pollution. This paper reviews the mechanisms of electron transport, redox, metabolism, structure, and composition of electroactive microorganisms in synthesizing energy materials. It then discusses and summarizes the applications of microbial energy materials in electrocatalytic systems, sensors, and power generation devices. Lastly, the research progress and existing challenges for electroactive microorganisms in the energy and environment sectors described herein provide a theoretical basis for exploring the future application of electroactive microorganisms in energy materials.

Application of Biomass Materials in Zinc-Ion Batteries.

Currently, aqueous zinc-ion batteries, with large reserves of zinc metal and maturity of production, are a promising alternative to sustainable energy storage. Nevertheless, aqueous solution has poor frost resistance and is prone to side reactions. In addition, zinc dendrites also limit the performance of zinc-ion batteries. Biomass, with complex molecular structure and abundant functional groups, makes it have great application prospects. In this review, the research progress of biomass and its derived materials used in zinc-ion batteries are reviewed. The different regulation strategies and characteristics of biomass used in zinc-ion battery electrodes, electrolyte separators and binders are demonstrated. The regulation mechanism is analyzed. At the end, the development prospect and challenges of biomass in energy materials application are proposed.

High-stretchable, self-healing, self-adhesive, self-extinguishing, low-temperature tolerant starch-based gel and its application in stimuli-responsiveness.

Starch with active hydroxyl groups is one of the most attractive carbohydrates for the preparation of gels in recent years. However, the mechanical properties, self-healing properties, self-adhesion properties, especially low-temperature resistance are generally unsatisfactory for current starch-based gels. Based on that, a multiple network structure of amylopectin-carboxymethyl cellulose-polyacrylamide (ACP) gel was prepared by a "cooking" method. Tannic acid (TA) was used to construct multiple hydrogen bonds among molecular chains. ACP gel demonstrates high elongation at break (1090 %) and strength, self-healing performance and adhesion behavior, extraordinary low-temperature resistance (-80 °C) and self-extinguishing. As a sensor device, ACP gel can effectively monitor human movements and microscopic expression changes and achieve real-time monitoring under harsh conditions (After multiple cutting-healing steps, under low-temperature conditions, even a month later). Additionally, ACP gel could be served to detect temperature changes with a wide operating range and a high sensitivity of 33 %·°C-1, which is promising to monitor the changes in temperature. More interestingly, ACP gel can even monitor the cooking process and breathing frequency with fast response, implying applications in food processing, disease diagnosis and medical treatment. This study provides new opportunities for the design and fabrication of carbohydrate-based gels with multiple performance and multifunctional electronic devices.

A Polyvinyl Alcohol-Tannic Acid Gel with Exceptional Mechanical Properties and Ultraviolet Resistance.

Design and preparation of gels with excellent mechanical properties has garnered wide interest at present. In this paper, preparation of polyvinyl alcohol (PVA)-tannic acid (TA) gels with exceptional properties is documented. The crystallization zone and hydrogen bonding acted as physical crosslinkages fabricated by a combination of freeze-thaw treatment and a tannic acid compound. The effect of tannic acid on mechanical properties of prepared PVA-TA gels was investigated and analyzed. When the mass fraction of PVA was 20.0 wt% and soaking time was 12 h in tannic acid aqueous solution, tensile strength and the elongation at break of PVA-TA gel reached 5.97 MPa and 1450%, respectively. This PVA-TA gel was far superior to a pure 20.0 wt% PVA hydrogel treated only with the freeze-thaw process, as well as most previously reported PVA-TA gels. The toughness of a PVA-TA gel is about 14 times that of a pure PVA gel. In addition, transparent PVA-TA gels can effectively prevent ultraviolet-light-induced degradation. This study provides a novel strategy and reference for design and preparation of high-performance gels that are promising for practical application.

A voice recognition-based digital cognitive screener for dementia detection in the community: Development and validation study.

Introduction: To facilitate community-based dementia screening, we developed a voice recognition-based digital cognitive screener (digital cognitive screener, DCS). This proof-of-concept study aimed to investigate the reliability, validity as well as the feasibility of the DCS among community-dwelling older adults in China. Methods: Eligible participants completed demographic, clinical, and the DCS. Diagnosis of mild cognitive impairment (MCI) and dementia was made based on the Montreal Cognitive Assessment (MoCA) (MCI: MoCA < 23, dementia: MoCA < 14). Time and venue for test administration were recorded and reported. Internal consistency, test-retest reliability and inter-rater reliability were examined. Receiver operating characteristic (ROC) analyses were conducted to examine the discriminate validity of the DCS in detecting MCI and dementia. Results: A total of 103 participants completed all investigations and were included in the analysis. Administration time of the DCS was between 5.1-7.3 min. No significant difference (p > 0.05) in test scores or administration time was found between 2 assessment settings (polyclinic or community center). The DCS showed good internal consistency (Cronbach's alpha = 0.73), test-retest reliability (Pearson r = 0.69, p < 0.001) and inter-rater reliability (ICC = 0.84). Area under the curves (AUCs) of the DCS were 0.95 (0.90, 0.99) and 0.77 (0.67, 086) for dementia and MCI detection, respectively. At the optimal cut-off (7/8), the DCS showed excellent sensitivity (100%) and good specificity (80%) for dementia detection. Conclusion: The DCS is a feasible, reliable and valid digital dementia screening tool for older adults. The applicability of the DCS in a larger-scale community-based screening stratified by age and education levels warrants further investigation.

Enhanced dielectric properties of polystyrene by using graphene incorporated styrene-butyl acrylate microspheres.

In view of the current trend of capacitor materials, the development of capacitors with high dielectric permittivity and low dielectric loss is of great interest. In this work, the dielectric permittivity of reduced graphene oxide-incorporated styrene-butyl acrylate (rGO@SBA) composite microspheres synthesized by mini-emulsion polymerization was significantly improved. rGO with 2 wt% content gave a dielectric permittivity of 11 356 (at 1 KHz), which was 1925 times higher than that of pure SBA (5.9). SEM and TEM were conducted to observe the morphology and structure of the composite microspheres. After filling into polystyrene (PS), a segregated structure of (rGO@SBA) that enables a concentrated aggregation of rGO in SBA was fabricated. The dielectric permittivity of PS could reach 10.91 (at 1 KHz) by incorporating only 0.39 wt% rGO by using this segregated structure of (rGO@SBA). PS simply mixed with SBA microspheres and graphite (PS/rGO-SBA) was also fabricated as a comparison group to verify the effect of this segregated structure on the dielectric properties of the composites. After comparing the dielectric properties of PS composites with different structures, the enhancement in dielectric permittivity of the composites can be demonstrated.

Ferroptosis-based molecular prognostic model for adrenocortical carcinoma based on least absolute shrinkage and selection operator regression.

BACKGROUND: This study aimed to find ferroptosis-related genes linked to clinical outcomes of adrenocortical carcinoma (ACC) and assess the prognostic value of the model. METHODS: We downloaded the mRNA sequencing data and patient clinical data of 78 ACC patients from the TCGA data portal. Candidate ferroptosis-related genes were screened by univariate regression analysis, machine-learning least absolute shrinkage, and selection operator (LASSO). A ferroptosis-related gene-based prognostic model was constructed. The effectiveness of the prediction model was accessed by KM and ROC analysis. External validation was done using the GSE19750 cohort. A nomogram was generated. The prognostic accuracy was measured and compared with conventional staging systems (TNM stage). Functional analysis was conducted to identify biological characterization of survival-associated ferroptosis-related genes. RESULTS: Seventy genes were identified as survival-associated ferroptosis-related genes. The prognostic model was constructed with 17 ferroptosis-related genes including STMN1, RRM2, HELLS, FANCD2, AURKA, GABARAPL2, SLC7A11, KRAS, ACSL4, MAPK3, HMGB1, CXCL2, ATG7, DDIT4, NOX1, PLIN4, and STEAP3. A RiskScore was calculated for each patient. KM curve indicated good prognostic performance. The AUC of the ROC curve for predicting 1-, 3-, and 5- year(s) survival time was 0.975, 0.913, and 0.915 respectively. The nomogram prognostic evaluation model showed better predictive ability than conventional staging systems. CONCLUSION: We constructed a prognosis model of ACC based on ferroptosis-related genes with better predictive value than the conventional staging system. These efforts provided candidate targets for revealing the molecular basis of ACC, as well as novel targets for drug development.

Advanced Metal-Organic Frameworks-Based Catalysts in Electrochemical Sensors.

Developing efficient catalysts is vital for the application of electrochemical sensors. Metal-organic frameworks (MOFs), with high porosity, large specific surface area, good conductivity, and biocompatibility, have been widely used in catalysis, adsorption, separation, and energy storage applications. In this invited review, the recent advances of a novel MOF-based catalysts in electrochemical sensors are summarized. Based on the structure-activity-performance relationship of MOF-based catalysts, their mechanism as electrochemical sensor, including metal cations, synthetic ligands, and structure, are introduced. Then, the MOF-based composites are successively divided into metal-based, carbon-based, and other MOF-based composites. Furthermore, their application in environmental monitoring, food safety control, and clinical diagnosis is discussed. The perspective and challenges for advanced MOF-based composites are proposed at the end of this contribution.

A Chewing Gum Residue-Based Gel with Superior Mechanical Properties and Self-Healability for Flexible Wearable Sensor.

Chewing gum residue is hard to decompose and easy to cause pollution, which is highly desirable to realize recycling. In this paper, a chewing gum gel with enhanced mechanical properties and self-healing properties is prepared by using polyvinyl alcohol (PVA) as the backbone in chewing gum residue. The hydrogen bond and the borax ester bond are employed to construct reversible interaction to enhance the self-healing ability. The physical crosslinking is realized by further freeze-thaw treatment to improve its mechanical properties. The gel demonstrates high elongation at break of 610% and strength of 0.11 MPa, as well as excellent self-healing performance and recyclable properties. In particular, the gel with a fast signal response is successfully applied as a wearable strain sensor to monitor different types of human motion. The gel as a sensor exhibits self-healing properties suggesting superior safety and stability, and displays wide linear sensitivity (the gauge factor is 0.417 and 0.170). The gel can be further served to explore temperature changes, implying the application in temperature monitoring. This study develops a novel approach for the recycle and reuse of chewing gum residue. The obtained gel may be a promising candidate for the fabrication of flexible wearable sensor.

Enhanced Toughness and Sound Absorption Performance of Bio-Aerogel via Incorporation of Elastomer.

In this study, Arabic gum/ carboxylic butadiene-acrylonitrite latex aerogels (AG/XNBRL) hybrid aerogel was successfully prepared by a green method, i.e., the combination of latex compounding and vacuum freeze-drying process. After that, the obtained composites were subjected to a high temperature treatment to crosslink the rubber phase. It was found that the AG in the AG/XNBRL hybrid aerogel could act as a framework to improve the dimensional stability of the aerogel, while the XNBRL phase could significantly improve the mechanical flexibility of the ensuing composite. Compared to the AG aerogel which is highly brittle in nature, the AG/XNBRL hybrid aerogel not only exhibits significantly enhanced toughness, but also shows improved thermal stability and sound absorption performances; for instance, the half weight loss (50%) temperature and average sound adsorption coefficient for aerogel containing 30 wt% XNBRL is 344 °C and 0.585, respectively, which are superior to those of neat AG aerogel. Overall, this work provides novel inspiration to prepare the mechanical robust bio-based aerogel for the sound absorption application.

A finalized determinant for complete lignocellulose enzymatic saccharification potential to maximize bioethanol production in bioenergy Miscanthus.

BACKGROUND: Miscanthus is a leading bioenergy crop with enormous lignocellulose production potential for biofuels and chemicals. However, lignocellulose recalcitrance leads to biomass process difficulty for an efficient bioethanol production. Hence, it becomes essential to identify the integrative impact of lignocellulose recalcitrant factors on cellulose accessibility for biomass enzymatic hydrolysis. In this study, we analyzed four typical pairs of Miscanthus accessions that showed distinct cell wall compositions and sorted out three major factors that affected biomass saccharification for maximum bioethanol production. RESULTS: Among the three optimal (i.e., liquid hot water, H2SO4 and NaOH) pretreatments performed, mild alkali pretreatment (4% NaOH at 50 °C) led to almost complete biomass saccharification when 1% Tween-80 was co-supplied into enzymatic hydrolysis in the desirable Miscanthus accessions. Consequently, the highest bioethanol yields were obtained at 19% (% dry matter) from yeast fermentation, with much higher sugar-ethanol conversion rates by 94-98%, compared to the other Miscanthus species subjected to stronger pretreatments as reported in previous studies. By comparison, three optimized pretreatments distinctively extracted wall polymers and specifically altered polymer features and inter-linkage styles, but the alkali pretreatment caused much increased biomass porosity than that of the other pretreatments. Based on integrative analyses, excellent equations were generated to precisely estimate hexoses and ethanol yields under various pretreatments and a hypothetical model was proposed to outline an integrative impact on biomass saccharification and bioethanol production subjective to a predominate factor (CR stain) of biomass porosity and four additional minor factors (DY stain, cellulose DP, hemicellulose X/A, lignin G-monomer). CONCLUSION: Using four pairs of Miscanthus samples with distinct cell wall composition and varied biomass saccharification, this study has determined three main factors of lignocellulose recalcitrance that could be significantly reduced for much-increased biomass porosity upon optimal pretreatments. It has also established a novel standard that should be applicable to judge any types of biomass process technology for high biofuel production in distinct lignocellulose substrates. Hence, this study provides a potential strategy for precise genetic modification of lignocellulose in all bioenergy crops.

A Highly Ionic Conductive, Healable, and Adhesive Polysiloxane-Supported Ionogel.

A new kind of polysiloxane-supported ionogel is successfully designed via locking ionic liquids (ILs), 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][Tf2 N]), into poly(aminopropyl-methylsiloxane) (PAPMS) grafted with [2-(methacryloyloxy)ethyl] trimethylammonium chloride (METAC) in the presence of tannic acid (TA). The novel ionogel exhibits good mechanical and recovery properties, as well as high ionic conductivity (1.19 mS cm-1 ) at 25 °C. In addition, the totally physical dual-crosslinked network based on ionic aggregates among METAC and the hydrogen bonds between PAPMS and TA provides excellent self-healing ability, which allows the damaged ionogel to almost completely heal (≈83%) in 12 h at room temperature. Interestingly, the obtained ionogel also shows satisfactory adhesive behavior to various solid materials. Moreover, this novel ionogel can maintain its high ionic conductivity and recovery property even at subzero temperatures. Therefore, this polysiloxane-supported ionogel is anticipated to be advantageous in flexible electronic devices such as sensors and supercapacitors, even at low temperatures.

Distinct polymer extraction and cellulose DP reduction for complete cellulose hydrolysis under mild chemical pretreatments in sugarcane.

In this study, liquid hot water (LHW) and chemical (H2SO4, NaOH, CaO) pretreatments were performed in Saccharum species including sugarcane bagasse. In comparison, the LHW and CaO pretreatments significantly enhanced biomass enzymatic hydrolysis, leading to much high bioethanol yield obtained at 19% (% dry matter) with an almost complete hexoses-ethanol conversion in the desirable So5 bagasse sample. Despite the LHW and CaO are distinctive for extracting hemicellulose and lignin, both pretreatments largely reduced cellulose degree of polymerization for enhanced lignocellulose enzymatic saccharification. Further chemical analysis indicated that the pretreated So5 sample had much lower cellulose crystalline index, hemicellulosic Xyl/Ara and lignin S/H ratio than those of other biomass samples, which explained that the So5 had the highest bioethanol yield among Saccharum species. Therefore, a mechanism model was proposed to elucidate how mild pretreatments could enhance biomass enzymatic saccharification for a high bioethanol production in the desirable sugarcane bagasse.

OB CITY-Definition of a Family-Based Intervention for Childhood Obesity Supported by Information and Communication Technologies.

Childhood obesity is becoming one of the 21st century's most important public health problems. Nowadays, the main treatment of childhood obesity is behavior intervention that aims at improve children's lifestyle to arrest the disease. Information and communication technologies (ICTs) have not been widely employed in this intervention, and most of existing ICTs systems are not having a long-term effect. The purpose of this paper is to define a system to support family-based intervention through a state-of-the-art analysis of family-based interventions and related technological solutions first, and then using the analytic hierarchy process to derive a childhood obesity family-based behavior intervention model, and finally to provide a prototype of a system called OB CITY. The system makes use of applied behavior analysis, affective computing technologies, as well as serious game and gamification techniques, to offer long term services in all care dimensions of the family-based behavioral intervention aiming to provide positive effects to the treatment of childhood obesity.

A sustainable woody biomass biorefinery.

Woody biomass is renewable only if sustainable production is imposed. An optimum and sustainable biomass stand production rate is found to be one with the incremental growth rate at harvest equal to the average overall growth rate. Utilization of woody biomass leads to a sustainable economy. Woody biomass is comprised of at least four components: extractives, hemicellulose, lignin and cellulose. While extractives and hemicellulose are least resistant to chemical and thermal degradation, cellulose is most resistant to chemical, thermal, and biological attack. The difference or heterogeneity in reactivity leads to the recalcitrance of woody biomass at conversion. A selection of processes is presented together as a biorefinery based on incremental sequential deconstruction, fractionation/conversion of woody biomass to achieve efficient separation of major components. A preference is given to a biorefinery absent of pretreatment and detoxification process that produce waste byproducts. While numerous biorefinery approaches are known, a focused review on the integrated studies of water-based biorefinery processes is presented. Hot-water extraction is the first process step to extract value from woody biomass while improving the quality of the remaining solid material. This first step removes extractives and hemicellulose fractions from woody biomass. While extractives and hemicellulose are largely removed in the extraction liquor, cellulose and lignin largely remain in the residual woody structure. Xylo-oligomers, aromatics and acetic acid in the hardwood extract are the major components having the greatest potential value for development. Higher temperature and longer residence time lead to higher mass removal. While high temperature (>200°C) can lead to nearly total dissolution, the amount of sugars present in the extraction liquor decreases rapidly with temperature. Dilute acid hydrolysis of concentrated wood extracts renders the wood extract with monomeric sugars. At higher acid concentration and higher temperature the hydrolysis produced more xylose monomers in a comparatively shorter period of reaction time. Xylose is the most abundant monomeric sugar in the hydrolysate. The other comparatively small amounts of monomeric sugars include arabinose, glucose, rhamnose, mannose and galactose. Acetic acid, formic acid, furfural, HMF and other byproducts are inevitably generated during the acid hydrolysis process. Short reaction time is preferred for the hydrolysis of hot-water wood extracts. Acid hydrolysis presents a perfect opportunity for the removal or separation of aromatic materials from the wood extract/hydrolysate. The hot-water wood extract hydrolysate, after solid-removal, can be purified by Nano-membrane filtration to yield a fermentable sugar stream. Fermentation products such as ethanol can be produced from the sugar stream without a detoxification step.

Poly[[(1,10-phenanthroline-κN,N')zinc]-µ-2,5-bis-(all-yloxy)terephthalato-κO:O].

The title compound, [Zn(C(14)H(12)O(6))(C(12)H(8)N(2))](n), is a coordination polymer forming one-dimensional infinite zigzag chains along [10[Formula: see text]] by inter-connection of Zn(II) atoms by 2,5-bis-(all-yl-oxy)-terephthalate anions via the carboxyl-ate groups. The Zn(II) atom is located on a twofold axis and is in a distorted tetra-hedral coordination formed by the two carboxyl-ate O atoms [Zn-O = 1.9647 (12) Å] and two phenanthroline N atoms [Zn-N = 2.0949 (14) Å].

Particle properties of sugar maple hemicellulose hydrolysate and its influence on growth and metabolic behavior of Pichia stipitis.

In this study the influence of the insoluble solids in nano-filtrated sugar maple hemicellulosic hydrolysate on the metabolic behavior of Pichia stiptis was investigated. The particle properties of hemicellulosic hydrolysate were analyzed. Phosphoric acid and ammonium (PA) were applied to remove the particles. The metabolic behavior and growth property of P. stipitis in particle--removed hydrolysate was measured. Results demonstrated that the average particle size and zeta potential of the untreated hydrolysate were 2266.9±78.2 nm and -6.09±0.49 mV. Xylose consumption and ethanol production rate were significantly decreased when particle content is greater than 1.63 g/L. Because the majority of particles (34 g/L) were removed from hydrolysates by phosphoric acid and ammonium treatment, the fermentability of the hydrolysate was significantly improved. These results indicated particles play an important role in hydrolysate inhibition effect.